for very helpful discussions. Interest Rates and the Durability of Consumption Goods

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钙钛矿类化合物铁磁性的产生原因

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versations and Professors H. A. Bethe and Kirkwood for several helpful discussions.

Why China’s_Economic_Reform_Differ：_the_M-Form_Hierarchy

The Economics of Transition, 1(2):135-170, June, 1993.Why China's Economic Reforms Differ:The M-Form Hierarchy and Entry/Expansion of the Non-State SectorbyYingyi Qian and Chenggang Xu1China's thirteen years of economic reforms (1979-1991) have achieved an average GNPannual growth rate of 8.6%. What makes China's reforms differ from those of EasternEurope and the Soviet Union is the sustained entry and expansion of the non-statesector. We argue that the organization structure of the economy matters. Unlike theirunitary hierarchical structure based on functional or specialization principles (the U-form), China's hierarchical economy has been the multi-layer-multi-regional one mainlybased on territorial principle (the deep M-form, or briefly, the M-form). Reforms havefurther decentralized the M-form economy along regional lines, which providedflexibility and opportunities for carrying out regional experiments, for the rise of non-state enterprises, and for the emergence of markets. This is why China's non-state sectorshare of industrial output increased from 22% in 1978 to 47% in 1991 and its privatesector's share from zero to about 10%, both being achieved without mass privatizationand changes in the political system.1. IntroductionRecently, there has been a revived interest among economists in China's economic reforms. Since 1979, economic reforms in China have generated a significant growth across the board: the overall performance of the Chinese economy has been better than its own past record, better than most developing countries at similar development levels, and also better than Eastern Europe and the former Soviet Union,1 Stanford University and London School of Economics, respectively. We would like to thank Philippe Aghion, Masahiko Aoki, Patrick Bolton, Avner Grief, Athar Hussain, Carla Krüger, Nicholas Lardy, John Litwack, Eric Maskin, John McMillan, Paul Milgrom, Dwight Perkins, Louis Putterman, Gerard Roland, Anna Seleny, Barry Weingast, Martin Weitzman, Jinglian Wu, and an anonymous referee for helpful discussions and comments. Qian's research is sponsored by the Center for Economic Policy Research (CEPR), the Hewlett Fund of the Institute of International Studies (IIS), and Center for East Asian Studies (CEAS) at Stanford University, and Xu's research is sponsored by the Center for Economic Performance (CEP) and the Suntory-Toyota International Center for Economics and Related Disciplines (STICERD) at London School of Economics.both before and after their radical transformations in 1989. It appears that China had no coherent reform programs, no commitment to private ownership, and no changes in the political system, and China's economy was still not fully liberalized. From both the theoretical and policy perspectives, China's different reform strategies and outstanding reform performances are particularly interesting and puzzling.The economic reforms in China formally started in 1979 following the Third Plenum of the Eleventh Congress of the Chinese Communist Party in December 1978. The starting time was later than that of Yugoslavia (1950) and Hungary (1968) and was about the same as for Poland (1980), and earlier than the Soviet Union (1986). Between 1979 and 1991, China's GNP grew at an average annual rate of 8.6%, or at 7.2% on the per capita basis.2 In 1992, the growth of GNP reached 12.8%.3 Exports grew at a faster pace, so that China's export-GNP ratio increased from below 5% in 1978 to nearly 20% in 1991.4 Also in this period, inflation was kept within a single-digit range except for three years (11.9% in 1985, 20.7% in 1988 and 16.3% in 1989); the household bank deposits to GNP ratio increased from 6% in 1978 to 46% in 1991; and the government budget deficit accounted for about 2-3% of GNP, about half of which was financed from bond issues (Table 1.1).Even more convincing evidence of the success of the reform is the increase in consumption and consumer durable goods by an average Chinese consumer in physical terms. For example, between 1978 and 1991, an average Chinese consumer increased his/her consumption about three times for edible vegetable oil, pork, and eggs (Table 1.2). In the rural areas, which account for about 75% of total population, the living space per person increased about 130% between 1978 and 1991 (Table 1.3). The2 Data sources in this paper are from Statistical Yearbook of China (various issues from 1985 to 1992), otherwise noted.3 Statistical Communique of the State Statistical Bureau on the 1992 National Economic and Social Development, February 18, 1992.4 The export-GNP ratios are calculated based on the official exchange rate and are upward biased. But the dramatic increase of export share in GNP during the reform is unmistaken.2average per household consumer durable goods, such as television sets, refrigerators and washing machines, also increased dramatically. For instance, in 1991, on average, every two rural households had one television set, and every urban household had more than one (Tables 1.4 and 1.5). There is no doubt that China is still a low-income developing country, but the evidence reveals clearly a substantial improvement in living standards due to economic reforms.The Chinese economic performance is in contrast to that of Eastern Europe and the former Soviet Union. Even if the two-digit annual decline of GNP in 1990 and 1991 in these countries was largely transitory, the magnitude was still too large to be ignored. What is more important, but tends to be neglected, is the economic stagnation in Eastern Europe and the Soviet Union in the decade of 1980s before the radical changes. According to official statistics, the average growth rate of GDP in Hungary was 1.8% between 1981 and 1985 and almost zero in 1988 and 1989. In Poland, the average GDP growth rate was less than 2% between 1981 and 1989.5 The situation in the Soviet Union was no better.Political considerations aside, two arguments often come into discussions on the differences between China and Eastern Europe. The first argument is about different levels of economic development: Eastern Europe and the Soviet Union were at a much higher development stage than China -- China had a very low per capita income with a dominant agriculture sector while the Eastern European and Soviet economies were "over-industrialized."6 The second argument is about different reform strategies: China has followed a gradual and piecemeal approach as opposed to the "big bang" strategy in most of after 1989 Eastern Europe and the former Soviet Union, like the shock therapy for stabilization in Poland and Russia,5 Data source for Hungary and Poland is from Table 9.1 of Kornai (1992).6 For example, Summers (1992) expressed this view when he highly praised China's reform performance. Sachs (1992) also expressed similar ideas during his interview with the Chinese Journal of Comparative Economic and Social Systems.3and fast and mass privatization in Czechoslovakia.7We feel that both views are relevant but unsatisfactory, or at least, are incomplete. China's level of industrialization was perhaps higher than most people would think. In 1978, China's gross industrial output value accounted for 62% of the total output value of society (35% in heavy industry and 27% in light industry), despite the fact that only 29% of the total labor force was employed in the non-agriculture sector. In terms of GNP, China's industry accounted for about half in 1978, as compared to 60% to 65% in Eastern Europe. Furthermore, in China, reforms have been more successful in the more industrialized regions with a weak central government control (like provinces of Guangdong, Jiangsu, and Zhejiang). Reforms have not been very successful in both the less industrialized regions (like the Northwest provinces) and the more industrialized regions with a strong central government control (like Shanghai and provinces of Liaoning and Jilin), the latter share similar problems of the earlier Hungarian reform. This fact suggests that one cannot explain the success of the reforms by low level of development alone.The argument for gradualism also raises more questions than answers. First, the agricultural reform in China proceeded very fast in the early 1980s. The abolishment of the commune system and the nationwide execution of the household responsibility system (an ownership reform) was implemented almost at one stroke, thus can be viewed as a big bang. More importantly, Eastern Europe's radical transition should not be examined in isolation: it came after deep troubles or failures of many years of gradual reform. In fact, the Hungarian reform started in 1968 with some initial success, but then ran into difficulties in the 1980s. Ironically, in several aspects China followed Eastern Europe's gradual reform measures. If China's gradualism is a success, why has it worked in China but not in Eastern Europe? On the other hand, why was China's success not a temporary one, and will China soon encounter problems similar to Hungary's?7 This view is reflected in Singh (1991), McMillan and Naughton (1992), and Chen, Jefferson and Singh (1992).4In this paper, we propose a theory to explain the differences between China's reforms and those of Eastern Europe and the Soviet Union. We first make an observation and provide extended evidence showing that, unlike the case of Eastern Europe and the Soviet Union, sustained entry and expansion of the non-state sector in China during the reforms were forceful and fast enough to become an important engine of growth by the end of the 1980s.8 We then theorize an institutional reason which is responsible for this phenomenal expansion and for the concurrent emergence of the market. We argue that the difference in the initial institutional conditions concerning the organizational structure of the planning hierarchy plays important roles in different transition paths of China and Eastern Europe and the former Soviet Union. The organization structures of both Eastern Europe and the Soviet Union were of a unitary form based on the functional or specialization principles (the "U-form" economy), and in contrast, the Chinese hierarchy has been of a multi-layer-multi-regional form mainly based on a territorial principle since 1958 (the "deep M-form" economy, or in short, the "M-form" economy). The M-form structure has been further decentralized along regional lines during reform with both increased authority and incentives for regional governments, which provided flexibility and opportunities for carrying out regional experiments, for the rise of non-state enterprises, and for the emergence of markets. Our institutional approach is able not only to incorporate and link together aspects of the arguments concerning the level of development and gradualism, but also to explain richer phenomena such as the successful use of experiments in China but not elsewhere.Under the M-form organization in China, interdependence between regional economies is not as strong as that of the U-form organization in Eastern Europe and the Soviet Union, because each region is relatively "self-contained." Unlike in Eastern Europe and the Soviet Union, regional governments in China (be it province, county, or township, village) have had considerable responsibility of coordination within the region. In particular, a large number of state-owned enterprises, including many in heavy industries, were8 We deliberately avoid the issue of the state sector. Evaluation of the reform in the state-sector has been controversial among China experts and Chinese economists.5subordinated under the regional governments even before the economic reforms. Hence, each region was relatively self-sufficient, the scale of an enterprise was small, and industries were less concentrated. In this environment, regional experiments can be carried out in a less costly way because the disruptive effect to the rest of the economy is minimal. A successful experiment in one region also has greater relevancy to other regions since adjacent regions are similar.When the M-form economy was further decentralized along regional lines in reform and the constraints on local government were gradually removed, the bottom level regional governments (i.e., townships and villages in the rural areas, and districts and neighborhoods in the urban areas) gained substantial autonomy in developing their own regions. They establish enterprises outside the state sector and outside the plan. From their inception, those non-state enterprises (most of them are not private though) have been market oriented. Furthermore, competition between regions for getting rich fast puts pressure on the local governments to concentrate on growth and their limited access to bank credits maintains discipline on their behavior. This explains how the rise of the non-state sector occurred by gradually weakening the existing hierarchical control without destroying the existing structure at one stroke.Of course, administrative decentralization induces, at the initial stage, costs of regional conflict, market protection, wasteful duplication, inefficient small scales of production and increased administrative intervention by local governments. We do not argue against these opinions but we would like to focus on a neglected but important aspect of benefits of a multi-layer-multi-regional form of organization, that is, the flexibility of the system for experiments and hence for institutional changes, and the opportunity provided to facilitate entry and expansion of the non-state sector outside the plan. The unexpected, and perhaps unintentional, growth of the non-state sector is critical for the success of China's economic reforms.Based on Chandler's seminal work (1966), Williamson (1975) first used the terms "U-form" and "M-form" in his study of business firms in the U.S. The U-form referred to the unitary organizational form6of the firm along functional lines in the second half of 1800s and early 1900s, while the M-form referred to the multi-divisional form of the firm organized by product, by technology, or by geography, which emerged since the 1920s. Compared with departments in the U-form firms, divisions in the multi-divisional firms are more self-contained, their responsibility for coordination and profit inside the division is high. The regional governments in our multi-layer-multi-regional structure economy share these features. However, our concept is not simply an application or an extension of the Chandler-Williamson's concept from firms to economies. There are important differences between the two concepts. In a multi-divisional firm, decentralization occurs exactly at the level of general office and the divisions, and each division is often organized by functions. In contrast, in our concept of the M-form economy, decentralization occurs at all levels of the hierarchy, that is, the M-form is deep. This is critically important: it is exactly because of the autonomy and incentives provided to the bottom levels of the regional governments in China, could the non-state sector grow so fast.The remaining part of the paper is organized as follows. Section 2 clarifies the definition of China's non-state sector and private sector. Section 3 provides empirical evidence on the sustained entry and expansion of the non-state sector between 1979 and 1991. Section 4 first characterizes institutions of the U-form hierarchies of Eastern Europe and the Soviet Union and the M-form hierarchy of China before the reform, and then describes several Chinese reform policies that are responsible for further decentralization along regional lines. Section 5 makes a general and preliminary analysis on the costs and benefits of the M-form organization vis-a-vis the U-form and the implications for transition. Section 6 explains specifically how the phenomenal expansion of the non-state sector in China is made possible under its M-form hierarchical organization. The final concluding section discusses implications of the non-state sector for further reforms in China and lessons from the Chinese experience for other economies in transition.72. What Is the Non-State Sector in China?92.1. The Non-State SectorBefore defining the non-state sector, we should first define the state sector. In China, by the constitution, the state-owned enterprises are owned by the "whole people." In practice, every state-owned enterprise is affiliated with one of the following four levels of government: (1) central; (2) provincial (with a population size of dozens of millions); (3) prefecture (with a population size of several millions); and (4) county (with a population size of several hundreds of thousands). A municipality is treated as one of the levels of province, prefecture or county, with a majority being at the level of a prefecture. Typically, the responsible government delegates the supervision of "its" state-owned enterprises to the industrial ministries/bureaus. Therefore, even for the state-owned enterprises, they are not homogeneous in terms of control.The non-state sector consists of all enterprises not in the state-sector, and it includes the private sector as a sub-sector. According to the location of its supervising government (if it has one), a non-state enterprise is designated as either an urban enterprise or a rural enterprise.10 By 1991, there were three categories of non-state ownership in China's official statistics: "collective ownership," "individual ownership," and "other types of ownership." Table 2.1 below provides a detailed picture with both official and alternative classifications:9 We only focus on the non-agriculture sector in this paper.10 An interesting and confusing fact is that many rural enterprises are located in urban areas. They are called "rural enterprises" simply because they are supervised by rural community governments (e.g. township or village governments) and the majority of their employees are not registered urban residents.8Table 2.1 China: Classification of the Non-State Sector(A) Collectives (jiti). Urban collectives include (i) enterprises that are affiliated with a district government under a municipality or a county ("large" collectives, dajiti); (ii) enterprises that are affiliated with a neighborhood under a district ("small" collectives, xiaojiti); and (iii) urban cooperatives (chengzhen hezuo). Many urban collectives are subsidiaries of state-owned enterprises which receive some transferred assets from the parent firms and hire their surplus employees or the employees' spouses and children. The advantages of subsidiaries being registered as collectives under the supervision of lower level government is less government control and more business flexibility.11Rural collectives include (i) enterprises that are affiliated with a township (xiang or zhen) government; (ii) enterprises that are affiliated with a village (cun) government; and (iii) rural cooperatives (nongcun hezuo). The predecessors of township and village enterprises (TVEs) were commune and brigade enterprises (CBEs) emerging during the Great Leap Forward in 1958. The ownership form of11 This is known as "one factory, two systems" (yichang liangzhi) in China, referring to the planned system for the state-owned part, and the market system for the collective part.9township and village enterprises is truly a Chinese invention that has not been found elsewhere.(B) Individual Business (geti). These are household/individual businesses hiring no more than 7 employees. An individual business has been allowed to operate since 1978.(C) Other Types of Ownership (qita leixing). This category includes mainly (i) private enterprises hiring more than 7 employees (siying); (ii) foreign enterprises and joint ventures with foreigners (sanzi qiye); and (iii) other types of joint ventures (e.g., a joint venture between state and private enterprises) and joint-stock companies. These types of ownership did not emerge until the early 1980s.122.2. The Private SectorDefining the non-state sector in China is easy, but defining the private sector is not. As seen above, a "private enterprise" is defined in China as a private business establishment hiring more than 7 employees. This narrow definition is on purpose, in order to circumvent ideological difficulties. For example, an individual/household hiring no more than 7 employees is classified as an "individual business," not as a "private enterprise," although it is certainly part of the private sector. So are sole foreign business establishments. As for joint ventures and joint-stock companies, strictly speaking, only those shares that are owned by foreigners and domestic private parties can be regarded as in the private sector.13 Some "cooperatives" are more like partnerships hiring many employees. This is especially true in Southern China, and in some areas they are called "joint stock cooperatives" (gufen hezuo). In addition, some township and village enterprises and urban district and neighborhood enterprises are de facto private12 If a state-owned enterprise is converted to a joint-stock company or limited liability company ("corporatization") or becomes a joint venture, it will be reclassified into the catagory of "others." As a result, it will not be regarded as "state-owned" anymore, despite the fact that the state may still own the majority interests. This may cause interpretation problems of the non-state sector in the future as more and more such a conversion occur starting in 1992.13 About one-half of "others" can be counted as truly private.10enterprises with vaguely defined ownership under the name of collectives.14Lacking further information and taking approximations, our definition of the private sector in China in this paper will include individual ownership, cooperative ownership, and other types of ownership under the official classification, and will exclude all of the township and village enterprises. We speculate that this should not give too much bias in either direction for data prior to 1992. The remaining part of the collectives, that is, enterprises affiliated with an urban district or neighborhood and with a rural township or village (TVEs), can be regarded as the community sector.3. Sustained Entry and Expansion of the Non-State Sector in China: Evidence3.1. General FeaturesFrom 1978 to 1991, the share of the non-state sector in national non-agriculture employment increased from about 40% to 57%. However, this happened not because of privatization or conversion of state enterprises to non-state enterprises. It is mainly due to entry and expansion of new non-state enterprises. In fact, employment by the state sector increased from 75 million in 1978 to 107 million in 1991. Its share declined because employment in the non-state sector grew even faster: from 21 million to 44 million in the urban area and from 28 million to 96 million in the rural during the same period.China's non-state sector is engaged in all kinds of activities: construction, transportation, commerce, service, and in particular, industry. This is perhaps a crucial difference between China's non-state sector and the private sector in Eastern Europe, particularly before 1989.15 During the period from14 For example, the famous computer company Stone Group is officially a "large collective" under Haidian district in the Beijing municipality, but actually run by a group of private businessmen. In Wenzhou municipality of the Zhejiang province, any business establishment with more than three co-owners is classified as a "collective," and is often called a "township" or "village" enterprise.15 See Kornai (1986) for the private sector development in Hungary before 1989.111981 to 1990, the national average annual growth rate of gross industrial output was 12.6%, in which the state sector grew at 7.7%, collectives at 18.7%, individual business at 92.2% and other types of ownership at 42.7%. As a result, the share of the non-state industry in the national total has expanded gradually from 22% in 1978 to 47% in 1991, and accordingly, the share of the state sector in industrial output shrunk from 78% to 53%. To put this into a historical perspective, the share of the state sector in 1991 is already below the level in 1957, which was 54% (Table 3.1).16The change of ownership composition of Chinese industry toward the non-state sector did not happen overnight. In fact, the process started before 1979. Although the true private industry in China did not appear until the early 1980s, the collectives had grown from 11% out of the national total in 1969 to 22% in 1978, or about one percent increase in output share every year (Table 3.1). However, the dramatic shift of weight toward the non-state sector has been apparent since 1979: The non-state sector in industry has on average experienced an increase in industrial share two percentage points every year for 13 years.17 Accompanied by the high growth rate, the non-state sector is also more efficient than the state sector. The annual growth rate of the total factor productivity of the non-state enterprises was much higher than that of the state enterprises.18 If one ranks all China's provinces according to their shares of the non-16 In 1957 the first five year plan was finished. At that time, there were still many state-private jointly-owned enterprises (gongsi heying). One year later, during the Great Leap Forward in 1958, the share of the state sector jumped to 90%.17 The Information Center of the State Planning Commission in China has already predicted that by the year 2000 only about one-quarter of industrial production will be produced by the state-sector in China. However, see footnote 11 for qualification to this statement.18 From 1982 to 1987, the annual growth rate of the total factor productivity of the TVEs is 12.5% at the national level, and 15% in the coastal areas (Xu, 1991). In contrast, from 1978 to 1985, the annual growth rate of the total factor productivity of the state-owned enterprises is 1.3% at the national level (Chen, et. al., 1988). Another piece of evidence comes from Xiao (1991). Using the provincial data from 1985 to 1987, Xiao shows a significant positive correlation between the total factor productivity of the provincial economies and the non-state sector share of the industrial output (with an exception of Shanghai).12state sector in industrial output, the top five, Zhejiang, Jiangsu, Guangdong, Shandong and Fujian, are precisely those provinces that have much higher growth than the national average.19 An interesting counter example of the coastal region is Shanghai. Shanghai was one of the most important financial and industrial centers in the Far East before 1949 and was also the industrial base after 1949. Shanghai has a low share of the non-state sector in industry as compared to the national average: 22% in 1985 and 32% in 1990. For the period from 1984 to 1989, Shanghai's industry grew only 7.9%, well below the national average. Shanghai's share of industrial output dropped from 10% in 1985 to only 6.8% in 1989, below that of Jiangsu, Shandong or Guangdong.Three additional characteristics about the entry and expansion of the non-state sector in China should be especially emphasized. First, the substantial entry and expansion occurred not because of an intentional design of a reform program from the central government, to the contrary, it came largely from the local initiatives. The central government's tolerance is mainly because it solves unemployment problems without much financial support from the state. Second, and related to the first, there has been a large variance in terms of organizational and developmental patterns of non-state-owned enterprises across regions. For example, while export and foreign investment have played important roles in some parts of Guangdong and Fujian, they are not so vital in many other high-growth provinces. On the other hand, township and village enterprises are a dominant force of the non-state sector in Jiangsu and Shandong, but individual, partnership and private enterprises are much more important in Zhejiang.Third, by 1991, the collectives and joint-ventures are the dominant majority of the non-state sector, and privately-owned enterprises played a minor role on the national scale. The collectives and joint-ventures have larger scale of operation, employ better technology, and absorb more human capital. This is because in China, there is still a lack of legal protection of private property rights, let alone commitment to19 These five provinces are all the coastal provinces. Because of the rapid growth, the share of industrial output of these five provinces in the national total rose from 30% in 1985 to 37% in 1990.13。

英语活动类作文带翻译

1. English Speech Contest
The English speech contest is a good opportunity to exercise oral expression and self-confidence. For example, the school organizes a themed speech contest, and students can choose topics of interest to express themselves orally. Not only can they improve their English speaking skills, but they can also exercise their thinking abilities and build self-confidence.
2. English Play Performance
Performing English plays is a good way to improve English speaking skills. By playing different characters, students can better understand and use English while also cultivating their teamwork and performance abilities.
范例：校园里最受欢迎的活动之一就是每周五下午的英语沙龙交流会，我们会在一起谈论英语电影、英语歌曲，还会进行一些英语游戏，不知不觉中就提高了自己的英语水平，也交到了很多朋友。
总的来说，参加各种形式的英语活动可以让学生们在轻松愉快的氛围中提高英语水平，培养兴趣，更好地理解和运用英语。希望同学们能积极参与，多多运用英语，不断提升自己的语言能力。

The Twin Crises The Causes of Banking and Balance-of-Payments Problems

Forthcoming in American Economic ReviewFirst Draft: December 1995This Version: November 9, 1998The Twin Crises: The Causes of Banking andBalance-of-Payments ProblemsGraciela L. Kaminsky Carmen M. Reinhart*AbstractIn the wake of the Mexican and Asian currency turmoil, the subject of financial crises has come to the forefront of academic and policy discussions. This paper analyzes the links between banking and currency crises. We find that: problems in the banking sector typically precede a currency crisis--the currency crisis deepens the banking crisis, activating a vicious spiral; financial liberalization often precedes banking crises. The anatomy of these episodes suggests that crises occur as the economy enters a recession, following a prolonged boom in economic activity that was fueled by credit, capital inflows and accompanied by an overvalued currency. (JEL F30, F41)* Graciela L. Kaminsky, George Washington University, Washington, D.C. 20552. Carmen M. Reinhart, University of Maryland, College Park, Maryland 20742. We thank two anonymous referees for very helpful suggestions. We also thank Guillermo Calvo, Rudiger Dornbusch, Peter Montiel, Vincent Reinhart, John Rogers, Andrew Rose and seminar participants at Banco de México, the Board of Governors of the Federal Reserve System, Florida State University, Harvard, the IMF, Johns Hopkins University, Massachusetts Institute of Technology, Stanford University, SUNY at Albany, University of California, Berkeley, UCLA, University of California, Santa Cruz, University of Maryland, University of Washington, The World Bank, and the conference on “Speculative Attacks in the Era of the Global Economy: Theory, Evidence, and Policy Implications,” (Washington, DC, December 1995), for very helpful comments and Greg Belzer, Kris Dickson, and Noah Williams for superb research assistance.Pervasive currency turmoil, particularly in Latin America in the late 1970s and early 1980s, gave impetus to a flourishing literature on balance-of-payments crises. As stressed in Paul Krugman’s (1979) seminal paper, in this literature crises occur because a country finances its fiscal deficit by printing money to the extent that excessive credit growth leads to the eventual collapse of the fixed exchange rate regime. With calmer currency markets in the mid- and late 1980s, interest in this literature languished. The collapse of the European Exchange Rate Mechanism, the Mexican peso crisis, and the wave of currency crises sweeping through Asia have, however, rekindled interest in the topic. Yet, the focus of this recent literature has shifted. While the earlier literature emphasized the inconsistency between fiscal and monetary policies and the exchange rate commitment, the new one stresses self-fulfilling expectations and herding behavior in international capital markets.1 In this view, as Guillermo A.Calvo (1995, page 1) summarizes “If investors deem you unworthy, no funds will be forthcoming and, thus, unworthy you will be.”Whatever the causes of currency crises, neither the old literature nor the new models ofself-fulfilling crises have paid much attention to the interaction between banking and currency problems, despite the fact that many of the countries that have had currency crises have also had full-fledged domestic banking crises around the same time. Notable exceptions are: Carlos Diaz-Alejandro (1985), Andres Velasco (1987), Calvo (1995), Ilan Goldfajn and Rodrigo Valdés (1995), and Victoria Miller (1995). As to the empirical evidence on the potential links between what we dub the twin crises, the literature has been entirely silent. The Thai, Indonesian, and Korean crises are not the first examples of dual currency and banking woes, they are only the recent additions to a long list of casualties which includes Chile, Finland, Mexico, Norway, and Sweden.In this paper, we aim to fill this void in the literature and examine currency and banking crises episodes for a number of industrial and developing countries. The former include: Denmark, Finland, Norway, Spain, and Sweden. The latter focus on: Argentina, Bolivia, Brazil, Chile, Colombia, Indonesia,1Israel, Malaysia, Mexico, Peru, the Philippines, Thailand, Turkey, Uruguay, and Venezuela. The period covered spans the 1970s through 1995. This sample gives us the opportunity to study 76 currency crises and 26 banking crises. Out-of sample, we examine the twin crises in Asia of 1997.Charles Kindelberger (1978, page 14), in studying financial crises, observes: “For historians each event is unique. Economics, however, maintains that forces in society and nature behave in repetitive ways. History is particular; economics is general.” Like Kindelberger, we are interested in finding the underlying common patterns associated with financial crises. To study the nature of crises, we construct a chronology of events in the banking and external sectors. From this timetable, we draw inference about the possible causal patterns among banking and balance-of-payments problems and financial liberalization. We also examine the behavior of macroeconomic indicators that have been stressed in the theoretical literature around crisis periods, much along the lines of Barry Eichengreen et. al. (1996a). Our aim is to gauge whether the two crises share a common macroeconomic background. This methodology also allows us to assess the fragility of economies around the time of the financial crises and sheds light on the extent to which the crises were predictable. Our main results can be summarized as follows:First, with regard to the linkages among the crises, our analysis shows no apparent link between balance of payments and banking crises during the 1970s, when financial markets were highly regulated. In the 1980s, following the liberalization of financial markets across many parts of the world, banking and currency crises become closely entwined. Most often, the beginning of banking sector problems predate the balance of payment crisis; indeed, knowing that a banking crisis was underway helps predict a future currency crisis. The causal link, nevertheless, is not unidirectional. Our results show that the collapse of the currency deepens the banking crisis, activating a vicious spiral. We find that the peak of the banking crisis most often comes after the currency crash, suggesting that existing problems were aggravated or new ones created by the high interest rates required to defend the exchange rate peg or the foreign exchange exposure of banks.2Second, while banking crises often precede balance of payments crises, they are not necessarily the immediate cause of currency crises, even in the cases where a frail banking sector puts the nail in the coffin of what was already a defunct fixed exchange rate system. Our results point to common causes, and whether the currency or banking problems surface first is a matter of circumstance. Both crises are preceded by recessions or, at least, below normal economic growth, in part attributed to a worsening of the terms of trade, an overvalued exchange rate, and the rising cost of credit; exports are particularly hard hit. In both types of crises, a shock to financial institutions (possibly financial liberalization and/or increased access to international capital markets) fuels the boom phase of the cycle by providing access to financing. The financial vulnerability of the economy increases as the unbacked liabilities of the banking system climb to lofty levels.Third, our results show that crises (external or domestic) are typically preceded by a multitude of weak and deteriorating economic fundamentals. While speculative attacks can and do occur as market sentiment shifts and, possibly, herding behavior takes over (crises tend to be bunched together), the incidence of crises where the economic fundamentals were sound are rare.Fourth, when we compared the episodes in which currency and banking crises occurred jointly to those in which the currency or banking crisis occurred in isolation, we find that for the twin crises, economic fundamentals tended to be worse, the economies were considerably more frail, and the crises (both banking and currency) were far more severe.The rest of the paper is organized as follows. The next section provides a chronology of the crises and their links. Section II reviews the stylized facts around the periods surrounding the crises while Section III addresses the issues of the vulnerability of economies around the time of the crisis and the issue of predictability. The final section discusses the findings and possibilities for future research.I. The Links Between Banking and Currency CrisesThis section briefly discusses what the theoretical literature offers as explanations of the possible3links between the two crises. The theoretical models also guide our choice of the financial and economic indicators used in the analysis.A. The links: theoryA variety of theoretical models have been put forth to explain the linkages between currency and banking crises. One chain of causation, stressed in James Stoker (1995), runs from balance of payments problems to banking crisis. An initial external shock, such as an increase in foreign interest rates, coupled with a commitment to a fixed parity will result in the loss of reserves. If not sterilized, this will lead to a credit crunch, increased bankruptcies, and financial crisis. Moreover, Frederic Mishkin (1996) argues that, if a devaluation occurs, the position of banks could be weakened further if a large share of their liabilities is denominated in a foreign currency. Models, such as Velasco (1987), point to the opposite causal direction--financial sector problems give rise to the currency collapse. Such models stress that when central banks finance the bail-out of troubled financial institutions by printing money, we return to the classical story of a currency crash prompted by excessive money creation.A third family of models contend that currency and banking crises have common causes. An example of this may be found in the dynamics of an exchange rate-based inflation stabilization plan, such as that of Mexico in 1987. Theory and evidence suggest that such plans have well-defined dynamics: 2 Because inflation converges to international levels only gradually, there is a marked cumulative real exchange rate appreciation. Also, at the early stages of the plan there is a boom in imports and economic activity, financed by borrowing abroad. As the current account deficit continues to widen, financial markets become convinced that the stabilization program is unsustainable, fueling an attack against the domestic currency. Since the boom is usually financed by a surge in bank credit, as banks borrow abroad, when the capital inflows become outflows and asset markets crash, the banking system caves in. Ronald I. McKinnon and Huw Pill (1996) model how financial liberalization together with microeconomic distortions--such as implicit deposit insurance--can make these boom-bust cycles even more pronounced by4fueling the lending boom that leads to the eventual collapse of the banking system. Ilan Goldfajn and Rodrigo Valdés (1995) show how changes in international interest rates and capital inflows are amplified by the intermediating role of banks and how such swings may also produce an exaggerated business cycle that ends in bank runs and financial and currency crashes.So, while theory does not provide an unambiguous answer as to what the causal links between currency and banking crises are, the models are clear as to what economic indicators should provide insights about the underlying causes of the twin crises. High on that list are international reserves, a measure of excess money balances, domestic and foreign interest rates, and other external shocks, such as the terms of trade. The inflation stabilization-financial liberalization models also stress the boom-bust patterns in imports, output, capital flows, bank credit, and asset prices. Some of these models also highlight overvaluation of the currency, leading to the underperformance of exports. The possibility of bank runs suggests bank deposits as an indicator of impending crises. Finally, as in Krugman (1979) currency crises can be the byproduct of government budget deficits.B. The Links: Preliminary EvidenceTo examine these links empirically, we first need to identify the dates of currency and banking crises. In what follows, we begin by describing how our indices of financial crises are constructed. Definitions, dates, and incidence of crisesMost often, balance of payments crises are resolved through a devaluation of the domestic currency or the floatation of the exchange rate. But central banks can and, on occasion, do resort to contractionary monetary policy and foreign exchange market intervention to fight the speculative attack. In these latter cases, currency market turbulence will be reflected in steep increases in domestic interest rates and massive losses of foreign exchange reserves. Hence, an index of currency crises should capture these different manifestations of speculative attacks. In the spirit of Eichengreen, et. al. (1996 a and b), we constructed an index of currency market turbulence as a weighted average of exchange rate changes and reserve changes.35With regard to banking crises, our analysis stresses events. The main reason for following this approach has to do with the lack of high frequency data that capture when a financial crisis is underway. If the beginning of a banking crisis is marked by a bank runs and withdrawals, then changes in bank deposits could be used to date the crises. Often, the banking problems do not arise from the liability side, but from a protracted deterioration in asset quality, be it from a collapse in real estate prices or increased bankruptcies in the nonfinancial sector. In this case, changes in asset prices or a large increase in bankruptcies or nonperforming loans could be used to mark the onset of the crisis. For some of the earlier crises in emerging markets, however, stock market data is not available.4 Indicators of business failures and nonperforming loans are also usually available only at low frequencies, if at all; the latter are also made less informative by banks’ desire to hide their problems for as long as possible.Given these data limitations, we mark the beginning of a banking crisis by two types of events: (1) bank runs that lead to the closure, merging, or takeover by the public sector of one or more financial institutions (as in Venezuela 1993); and (2) if there are no runs, the closure, merging, takeover, orlarge-scale government assistance of an important financial institution (or group of institutions), that marks the start of a string of similar outcomes for other financial institutions (as in Thailand 1996-97). We rely on existing studies of banking crises and on the financial press; according to these studies the fragility of the banking sector was widespread during these periods. This approach to dating the beginning of the banking crises is not without drawbacks. It could date the crises too late, because the financial problems usually begin well before a bank is finally closed or merged; it could also date the crises too early, because the worst of crisis may come later. To address this issue we also date when the banking crisis hits its peak, defined as the period with the heaviest government intervention and/or bank closures.Our sample consists of 20 countries for the period 1970-mid-1995. The countries are those listed in the introduction and Appendix Tables 1 and 2. We selected countries on the multiple criteria of being small open economies, with a fixed exchange rate, crawling peg, or band through portions of the sample;6data availability also guided our choices. This period encompasses 26 banking crises and 76 currency crises.As to the incidence of the crises (Table 1 and Figure 1), there are distinct patterns across decades. During the 1970s we observe a total of 26 currency crises, yet banking crises were rare during that period, with only 3 taking place. The absence of banking crises may reflect the highly regulated nature of financial markets during the bulk of the 1970s. By contrast, while the number of currency crises per year does not increase much during the 1980s and 1990s (from an average of 2.60 per annum to 3.13 per annum, Table 1, first row), the number of banking crises per year more than quadruples in the post-liberalization period. Thus, as the second row of Table 1 higlights, the twin crisis phenomenon is one of the 1980s and 1990s.Figure 1 also shows that financial crises were heavily bunched in the early 1980s, when real interest rates in the United States were at their highest level since the 1930s. This may suggest that, external factors, such as interest rates in the United States, matter a great deal as argued in Calvo, et. al. (1993). Indeed, Jeffrey Frankel and Andrew K. Rose (1996) find that foreign interest rates play a significant role in predicting currency crashes. A second explanation why crises are bunched is that contagion effects may be present, creating a domino effect among those countries that have anything less than immaculate fundamentals. Sara Calvo and Reinhart (1996) present evidence of contagion in capital flows to Latin American countries while Eichengreen, et. al.(1996b) find evidence that knowing there is a crisis elsewhere increases the probability of a domestic currency crisis.Table 2 provides the dates of financial liberalization, the beginning and peak of the banking crisis, and the date of the balance of payments crisis that was nearest to the beginning of the banking crisis.5 By selecting the nearest currency crisis, whether it predates or follows the beginning of the banking crisis, we allow the data to reveal what the temporal patterns are. The dates for the remaining crises are given in the Appendix tables.The twin crises7We next examine how the currency and banking crises are linked. We begin by calculating the unconditional probability of currency crises and banking crises in our sample. For instance, the probability that a currency crisis will occur in the next 24 months over the entire sample is simply 24 times 76 (the total number of currency crises in the sample) divided by the total number of monthly observations in the sample. These calculations yield unconditional probabilities for currency and banking crises, which are twenty nine percent and ten percent, respectively (Table 3). The difference in the probabilities of the two kinds of crises highlights the relatively higher frequency of currency crises in the sample.We next calculate a family of conditional probabilities. For instance, if knowing that there is a banking crisis within the past 24 months helps predict a currency crisis then, the probability of a currency crisis, conditioned on information that a banking crisis is underway, should be higher than the unconditional probability of a balance of payments crisis. In other words, a banking crisis increases the probability that a country will fall prey to a currency crisis. This is precisely what the results summarized in Table 3 show. The probability of a currency crisis conditioned on the beginning of banking sector problems is 46 percent, well above the unconditional estimate 29 percent. Hence, it could be argued, as Diaz Alejandro (1985) and Velasco (1987) did for the Chilean crisis in the early 1980s, that, in an important number of cases, the bail-out of the banking system may have contributed to the acceleration in credit creation observed prior to the currency crises (see Herminio Blanco and Peter M. Garber (1986), Sebastian Edwards (1989), and Eichengreen et. al. (1996a), and this paper). Even in the absence of a large-scale bail-out, a frail banking system is likely to tie the hands of the central bank in defending the currency--witness Indonesia in August 1997.If, instead, the peak of the banking crisis is used as the conditioning piece of information, no valuable information is gained; indeed, the conditional probability is 22 percent and below the unconditional. This result follows from the fact that a more common pattern (see Table 2) appears to be that the peak of the banking crisis comes after the currency crisis. For instance, knowing that there is a8currency crisis does not help predict the onset of a banking crisis, this conditional probability is 8 percent; knowing that there was a currency crisis does help to predict the probability that the banking crisis will worsen, this conditonal probability is 16 percent.Taken together, these results seem to point to the existence vicious circles. Financial sector problems undermine the currency. Devaluations, in turn, aggravate the existing banking sector problems and create new ones. These adverse feedback mechanisms are in line with those suggested by Mishkin (1996) and can be amplified, as we have seen in several of the recent Asian crises, by banks’ inadequate hedging of foreign exchange risk. The presence of vicious circles would imply that, a priori, the twin crises are more severe than currency or banking crises that occur in isolation.To measure the severity of a currency crisis, we focus on a composite measure that averages reserve losses and the real exchange rate depreciation.6 For reserves, we use the six-month percent change prior to the crisis month, as reserve losses typically occur prior to the devaluation (if the attack is successful). For the real exchange rate, we use the six-month percent change following the crisis month, because large depreciations occur after, and only if, the central bank concedes by devaluing or floating the currency. This measure of severity is constructed for each currency crisis in our sample and the averages are reported in Table 4 separately for the 19 twin crises in our sample and for the others. In line with our results that the beginning of the banking crisis precedes the balance of payments crisis, we define the twin crises as those episodes in which a currency crisis follows the beginning of the banking crisis within the next 48 months. For banking crises, we use the bail-out costs, as a percent of GDP, as the measure of severity. As Table 4 highlights, bail-out costs are significantly larger (more than double) in the twin crises than for banking crises which were not accompanied by a currency crisis. As to balance of payments crises, the results are mixed. Reserve losses sustained by the central bank are significantly bigger (Table 4) but the real depreciations are of comparable orders of magnitude.Our results also yield an insight as to the links of crises with financial liberalization (Table 3). In918 of the 26 banking crises studied here, the financial sector had been liberalized during the preceding five years, usually less. Only in a few cases in our sample countries, such as the early liberalization efforts of Brazil in 1975 and Mexico in 1974, was the liberalization not followed by financial sector stress. In the 1980s and 1990s most liberalization episodes have been associated with financial crises of varying severity. Only in a handful of countries (for instance, Canada which is not in the sample) did financial sector liberalization proceed smoothly. Indeed, the probability of a banking crisis (beginning) conditional on financial liberalization having taken place is higher than the unconditional probability of a banking crisis. This suggests that the twin crises may have common origins in the deregulation of the financial system and the boom-bust cycles and asset bubbles that, all too often, accompany financial liberalization. The stylized evidence presented in Gerald Caprio and Daniela Klingebiel (1996) suggests that inadequate regulation and lack of supervision at the time of the liberalization may play a key role in explaining why deregulation and banking crises are so closely entwined.II. The Macroeconomic Background of the CrisesTo shed light on whether both types of crises may have common roots, we analyze the evolution of 16 macroeconomic and financial variables around the time of the crises. The variables used in the analysis were chosen in light of theoretical considerations and subject to data availability. Monthly data was usedto get a clearer view (than would otherwise be revealed by lower frequency data) of developments as the crisis approaches and by the desire to evaluate to what extent these indicators were giving an early signal of impending trouble--an issue that will be taken up in the next section.The indicators associated with financial liberalization are the M2 multiplier, the ratio of domestic credit to nominal GDP, the real interest rate on deposits, and the ratio of lending-to-deposit interest rates. Other financial indicators include: excess real M1 balances, real commercial bank deposits, and the ratioof M2 (converted into U.S. dollars) divided by foreign exchange reserves (in U.S. dollars).7 The indicators linked to the current account include the percent deviation of the real exchange rate from trend, as a10measure of misalignment, the value of exports and imports (in U.S. dollars), and the terms-of-trade.8 The indicators associated with the capital account are: foreign exchange reserves (in U.S. dollars) and the domestic-foreign real interest rate differential on deposits (monthly rates in percentage points). The indicators of the real sector are industrial production and an index of equity prices (in U.S. dollars). 9 Lastly, the fiscal variable is the overall budget deficit as a percent of GDP.Of course, this is not an exhaustive list of potential indicators. In particular, political variables, such as the timing of an election, can also be linked to the timing of these crises. Indeed, the evidence presented in Deepak Mishra (1997), who examines a subset of the currency crises in this study, suggests that devaluations, more often than not, follow elections. Indeed, an election raises the probability of a future devaluation, even after controlling for economic fundamentals.Except for the interest rate variables, the deviations of the real exchange rate from trend, our proxy for excess real M1 balances, and the lending/deposit interest rates ratio, which are in levels, we focus on the 12-month percent changes of the remaining 10 variables. The pre- and post-crises behavior of all variables is compared to the average behavior during tranquil periods, which are all the remaining observations in our sample and serves as our control group.Figures 2, 3, and 4 illustrate the behavior of the variables around the time of the balance of payments, banking crises, and twin crises, respectively; each panel portrays a different variable. The horizontal axis records the number of months before and after the beginning of the crises; the vertical axis records the percent difference (percentage point difference for interest rates) between tranquil and crisis periods. In all the figures the solid line represents the average for all the crises for which data was available.10 Hence, if no data points are missing, the solid line represents the average behavior of that indicator during the months around 76 currency crises and 26 banking crises. For Figures 2 and 3, the dotted lines denote plus/minus one standard error around the average. For example, the top center panel of Figure 2 shows that, on average, the 12-month growth in the domestic credit/GDP ratio is about 15 percent11higher than in tranquil times. In Figure 4 the solid line shows the evolution of the indicators for the twin crises episodes while the dashed line denotes the averages for the currency crises that were not accompanied by a banking crisis.For currency crises we focus on the 18-month period before and after the crisis. Unlike balance of payments crises, in which reserves are lost abruptly and currency pegs abandoned, banking crises are protracted affairs which tend to come in waves and, hence, the depth of the crisis is seldom reached at the first sign of outbreak (see Table 2). For this reason, we widen the window and focus on the 18 months before the onset of the crisis, a 18-month arbitrarily chosen crisis period, and the 18 months post-crisis period. At any rate, because most of our analysis focuses on the causes leading up to the crises, our main results will not be affected whether the crises lasted less or more than a year. For the 19 episodes of the twin crises, we focus on the 18 months prior to the balance of payments crisis. Given that banking crises usually predate currency crises in our sample, this implies we are already looking at a period of heavy financial sector stress.A. The Financial SectorUntil the 1970s, most financial markets were regulated with rationed credit and, often, negative real interest rates. The late 1970s and beginning of the 1980s, however, witnessed sweeping financial reforms both in developed and emerging markets, which led to, among other things, increases in real interest rates. 11 Because financial liberalization often precedes banking crises--the indicators associated with financial liberalization presented in the first four panels of Figures 2, 3, and 4 (from left to right) merit scrutiny. The growth in the M2 multiplier rises steadily up to nine months prior to the currency crisis and the onset of the banking crisis; indeed, for banking crises the multiplier grows at above normal rate in the entire 18 months prior to the crisis. The draconian reductions in reserve requirements that often accompany financial liberalization play a role in explaining the large increases in the M2 multiplier. Yet the rise in the multiplier prior to currency crises is entirely accounted for by its evolution ahead of the twin12。

给国外客人的感谢信

给国外客人的感谢信dear ____________,please excuse my delay in thanking you for your hospitality during our visit to your firm on ____________ [date].i found our discussions very helpful and encouraging. we now have a better understanding of your needs and will soon submit another proposed contract for your approval. we expect to have it ready by ____________ [date].again, thank you for the pleasant visit.yours sincerely,____________ [name]____________ [ ]尊敬的__________，我们于__________[日期]拜访了贵公司，您的热情款待让我们十分感激，在此请您接受我们这份迟到的谢意。

我们的`讨论是十分有益且令人鼓舞的。

我们现已进一步了解了您的需求，并将很快向您呈上一份新的合同提议供您批阅，#url#预计该提议将于______[日期]前完成。

再次感谢您为我们安排的这次愉快的访问。

此致，__________[姓名]__________[头衔]s(“content_relate”);【给国外客人的感谢信】相关文章：1.酒店给客人的感谢信2.回复客人的感谢信3.国外老客户来访感谢信4.酒店对客人的感谢信5.给国外工作者的感谢信的范文6.欢迎客人的祝酒词7.致客人的道歉信8.给客人的道歉信9.对客人的慰问信。

讨论益处的作文模板英文

讨论益处的作文模板英文英文回答：There are numerous benefits to discussing a topic.First and foremost, it allows individuals to gain a deeper understanding of the subject matter. When we engage in discussions, we have the opportunity to share our thoughts, perspectives, and knowledge with others. This exchange of ideas helps us to expand our own understanding and learn from different viewpoints. For example, in a literature class, discussing a novel with classmates can provide uswith new insights and interpretations that we may not have considered on our own.Additionally, discussing a topic can enhance ourcritical thinking skills. Through conversations and debates, we are challenged to analyze and evaluate different arguments and evidence. This process of questioning and reasoning helps us to develop our own opinions and make informed decisions. For instance, in a business meeting,discussing the pros and cons of a particular strategy can lead to a more well-rounded and thoughtful decision-making process.Furthermore, discussing a topic can fostercollaboration and teamwork. When we engage in discussions, we are able to work together towards a common goal. By sharing ideas and brainstorming, we can come up with innovative solutions and strategies. This collaborative approach not only improves the quality of our work, butalso strengthens our relationships with others. For example, in a group project, discussing the project requirements and dividing tasks can lead to a more efficient and successful outcome.In conclusion, discussing a topic brings numerous benefits. It helps us to gain a deeper understanding, enhances our critical thinking skills, and fosters collaboration. Through discussions, we can learn from others, develop our own opinions, and work together towards common goals.中文回答：讨论一个话题有很多好处。

RH问题

1. Introduction It is a common problem in the numerical treatment of partial diﬀerential equations (PDEs) that most of the PDEs appearing in applications are deﬁned on Rd where d is the dimension, i.e., on unbounded domains, whereas computers are generally able to deal with only ﬁnite domains. One popular approach in this context is to set up the problem on a ﬁnite domain and to impose transparent boundary conditions (TBC) which give the boundary data which would appear at this location if the initial value problem where treated on the whole Rd , or artiﬁcial boundary conditions approximating TBC. To this end a certain relation between Dirichlet and von Neumann data at the boundary has to be satisﬁed called the Dirichlet to von Neumann map, see e.g. [15, 31] for reviews of TBC approaches and in particular [1] for Schrödinger equations. An alternative approach is given by perfectly matched layers (PML) which were introduced by Bérenger [5] for the Maxwell equations. The idea is to join absorbing layers at the boundaries of the computational domain. The to be solved PDE is deformed in the layers in a way that the solution in the computational domain is not aﬀected, and that it is rapidly dissipated in the layers. This PML approach was adapted to various equations, see for instance [26, 16] for Schrödinger equations. We use here the approach [36] that is similar to exterior complex scaling methods [25]. An interesting approach to treat PDEs on unbounded domains is to map inﬁnite domains to ﬁnite domains. In a numerical context, this was apparently ﬁrst used in [27] and later for the Schrödinger equation in [22]. Whereas [22] uses a ﬁnite diﬀerence method, [27] incorporates one of the ﬁrst applications of a spectral

会展经济与管理新媒体营销中英文对照外文翻译文献

中英文对照外文翻译(文档含英文原文和中文翻译)原文:Social Networks and the Mass MediaAdapted from: American Political Science Review,2013,107 Social networking has become an every day part of many peoples’lives as evidenced by the huge user communities that are part of such networks. Facebook, for instance, was launched in February 2004 by Harvard under graduate students as an alternative to the traditional stud ent directory. In tended to cover interaction between students at Univers ities–Facebook enables individuals to encourage others to joint he network through personalized invitations, friend suggestions and creation of s pecialist groups. Today Facebook has a much wider take up than just s tudents at Universities. Facebook now facilitates interaction between peo ple by enabling sharing of common interests, videos, photos, etc. Sharin g,Some social network populations exceed that of large countries, for example Facebook has over 350 million active users. Social networks provide a platform to facilitate communication and sharing between user s, in an attempt to model real world relationships. Social networking ha s now also extended beyond communication between friends; for instanc e, there are a multitude of integrated applications that are now made a vailable by companies, and some organizations use such applications, su ch as Facebook Connect to authenticate users, i.e. they utilize a user’s Facebook credentials rather than requiring their own credentials(for exa mple the Calgary Airport authority in Canada uses Facebook Connect t o grant access to their WiFi network). This ability to combine a third party application (including its local data) to authenticate users demonstr ates the service-oriented approach to application development. By tappin g into an already established community around a particular social netw orking platform, it becomes unnecessary to require users to register wit h another system.The structure of a Social Network is essentially the formation of a dynamic virtual community with inherent trust relationships between fri ends. (Szmigin et al., 2006) identify how “relationship marketing” (ident ified as referring to all marketing activities directed towards establishing, developing and maintaining successful relational exchanges) can be faci litated through the creation of on-line communities. They discuss how o n-line communities can be used to facilitate interaction and bonding bet ween consumer and suppliers, intermediate parties and specific brands. Similarly, (Shang et al., 2006) discuss how brand loyalty can be achiev ed through various types of participation within an on-line community (focusing specifically on the –a virtual communit y of Apple users in Taiwan). They discuss the motivation for individua ls to promote certain products during on-line discussions (active particip ants) and for others to remain as lurkers (passive participants). The stu dy particularly focuses on the incentives for participants to contribute to an on-line community, based on the perception of a user about the de gree of relevance towards an object that is being discussed –focusing on both cognitive (based on utilitarian motive –concerning an individua l’s concern with the cost and benefit of the product or service) and aff ective (a value-expressive motive, referring to an individual’s interest in enhancing self-esteem or self-conception, and in projecting his/her desir ed self-image to the outside world through the product or service).It is also useful to understand, for instance, how such trust relation ships could be used as a foundation for resource (information, hardware, services) sharing. Cloud environments are typically focused on providin g low level abstractions of computation or storage. Using this approach, a user is able to access (on a short term/rental basis) capacity that is owned by another person or business (generally over a computer networ k). In this way, a user is able to outsource their computing requirement s to an external provider –limiting their exposure to cost associated wi th systems management and energy use. Computation and Storage Clou ds are complementary and act as building blocks from which applicatio ns can be constructed –using a technique referred to as “mash-ups”. S torage Clouds are gaining popularity as a way to extend the capabilities of storage-limited devices such as phones and other mobile devices. T here are also a multitude of commercial Cloud providers such as Amaz on EC2/S3, Google App Engine, Microsoft Azure and also many smalle r scale open clouds like Nimbus (Keahey et al., 2005) and Eucalyptus (Nurmi et al., 2009). A Social Cloud (Chard et al., 2010), on the other hand, is a scalable computing model in which virtualized resources co ntributed by users are dynamically provisioned amongst a group of frie nds. Compensation for use is optional as users may wish to share reso urces without payment, and rather utilize a reciprocal credit (or barter) based model (Andrade et al., 2010). In both cases guarantees are offered through customized Service Level Agreements (SLAs). In a sense, thi s model is similar to a Volunteer computing approach, in that friends s hare resources amongst each other for little to no gain. However, unlik e Volunteer models there is inherent accountability through existing frie nd relationships. There are a number of advantages gained by leveraging social networking platforms, in particular one can gain access to hug e user communities, can exploit existing user management functionality, and rely on pre-established trust formed through existing user relations hips.The author thanks Jason Barabas, Jon Bendor, Ted Carmines, Jami e Druckman, John Freeman, Matt Golder, Sona Golder, Bob Jackson, J enn Jerit, Kris Kanthak, ?zge Kemahlioglu, Charlotte Lee, Valerie Marti nez-Ebers, Adam Meirowitz, Scott McClurg, Will Moore, Chris Reenock, John Ryan, John Scholz, Jake Shapiro, Anand Sokhey, Jeff Staton, Ji m Stimson, Craig Volden, Jon Woon, four very helpful anonymous revi ewers, and audiences in the Political Economics group at the Stanford GSB, Political Science departments at FSU, GWU, Minnesota, Pittsburg h, and Stony Brook, and the Frank Batten School of Leadership and P ublic Policy at UVa. Any errors are my own.To begin to answer this question, I develop a novel theory of aggr egate opinion and behavior. The theory considers a heterogeneous popul ation of individuals who must choose between dichotomous options. It incorporates the interaction of social network and mass media influences at the individual level; its key assumption is that the more others cho ose an option, the more one is apt to do so as well. In the theory, soc ial networks provide information about the choices of those to whom o ne is directly connected, while the mass media provide (potentially bias ed) information about aggregate choice. The theory thus applies to, for example, voter turnout and political participation (e.g., Gerber, Green, a nd Larimer 2008; Lake and Huckfeldt 1998; Leighley 1990; McClurg 2 003; Rolfe 2012), opinion formation (e.g., Beck et al. 2002; Druckman and Nelson 2003; Huckfeldt and Sprague 1995), protests and social mo vements (e.g., Kuran 1991; McAdam 1986), and vote choice (e.g., Beck 2002; Huckfeldt and Sprague 1995; Ryan 2011; Sinclair 2012; Sokhey and McClurg 2012).Three major results follow from this theory. All hold both when in dividuals treat media identically and when they select into media in lin e with their preferences. First, understanding the aggregate effect of the media generally requires considering social networks, because social ne twork structure conditions media's impact. For example, additional weak ties between disparate social groups can reduce the media's impact, an d the presence of unified social elites can eliminate the media's impact entirely in the aggregate. Empirical studies of media impact that fail t o consider media's interaction with social networks risk bias.Second, social networks can amplify the effect of media bias. A bi ased media outlet that systematically under- or over-reports a poll of th e population by a only a few percentage points can in some cases swi ng aggregate behavior (e.g., turnout or vote share) by over 20% in eith er direction due to positive feedback within the network. Open advocate s in the media can have a yet larger impact even when not comparativ ely influential. Unified social elites limit the effect of media bias, but c annot fully counter an advocate; selection into media, made ever easier with technological improvements, tends to enhance the effect of bias. We should therefore expect media bias to become increasingly importan t to aggregate behavior.AN INDIVIDUAL-LEVEL THEORY OF AGGREGATE BEHAVIO RThough I present a theory of aggregate behavior, it is based on in dividual-level assumptions informed by what we know about the way p ersonal characteristics, social networks, and mass media outlets affect in dividual behavior. Due to this, the theory can explore the effect that int eractions between these three factors have on aggregate behavior. As i mportantly, the theory incorporates empirically realistic heterogeneity acr oss people in allthree factors.Additionally, people are exposed to individuals, groups, and organiz ations external to one's network, such as mass media outlets, state prop aganda, national party leaders, NGOs, and Internet personalities. These outlets can provide information, increasing political knowledge.As this small sampling of large literatures indicates, individuals' de cisions are influenced by the information they obtain via both local soc ial networks and global media outlets. However, comparatively little sch olarship has explored the three-way interaction of personal characteristic s, social networks, and mediaIn the second type of bias, which I call advocacy, the media outle t simply states a preference for one of the options, providing no inform ation about aggregate support. The goal in advocacy is to sway the po pulation toward one or the other option. As before, many goals could u nderlie advocacy beyond just the support of a biased media outlet's pre ferences. Advocacy represents the editorial power of the media or the i nfluence of an external actor; it is a "one-message" model (Zaller 1992).I focus my analysis in all three sections on the case in which one of the two options is the status quo, and all individuals begin supporti ng it. For political participation and social movements, the status quo is not participating. For opinion formation and vote choice, the status qu o is an existing option such as a policy in place or an incumbent politician, as contrasted with an alternative such as a newly proposed policy or a challenging politician. For simplicity I subsequently call participat ion the option that is not the status quo; this should be read as "partici pation in support of" the option that is not the status quo in contexts o ther than political participation or social movements.In my analysis I simultaneously vary media strength, network prop erties, media bias, and, for two outlets, the strength of the L outlet. Th ough I keep my analysis to two biased outlets, it can easily be extende d to multiple biased outlets with the addition of parameters dictating th eir relative strengths.二、译文社交网络和大众传媒社交网络已经成为许多人每天生活的一部分，即证明了这种网络庞大的用户群体。

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Interest Rates and the Durability of ConsumptionGoodsHarry Mamaysky∗This Draft:March11,2001Comments Welcome∗Yale School of Management,135Prospect St.,Box208200,New Haven,CT,06520-8200.Email: harry.mamaysky@.Phone:(203)436-0649.Fax:(203)436-0630.I would like to thank Hua He, Jonathan Ingersoll,Andrew Jeﬀrey,Leonid Kogan,Geert Rouwenhorst,Matthew Spiegel,and Raman Uppal for very helpful discussions.Interest Rates and the Durability of ConsumptionGoodsAbstractIn this article I study an economy with irreversible durable investment and investors who consume a durable and a nondurable good.In equilibrium,these assumptions lead to endoge-nous variation in the implied risk aversion of investors.This in turn causes the short term interest rate,the exchange rate between the two goods,and the term structure of interest rates toﬂuctuate stochastically.I investigate the connection between theseﬁnancial vari-ables and investment into the durable good,and provide one explanation for several features of the empirical relationship between interest rates and the business cycle.Additionally,I derive a closed form asymptotically valid solution of the model.Using U.S.GNP and government bond data,I test several implications of the model.As predicted by the model,Iﬁnd that the fraction of GNP devoted to durable consumption is (1)procyclical,(2)able to forecast future GNP growth,(3)able to forecast the future term spread,and(4)able to forecast future excess returns on long term bonds.The model and the data suggest that a fundamental link exists between durable consumption and interest rates.JEL Classiﬁcation:G12Contents1Introduction1 2The Model72.1A Pareto Optimal Allocation (8)2.2Discussion of the Model (9)3The Equilibrium103.1An Agent’s Control Problem (10)3.2The Optimal Investment Policy (13)3.3The Price of Durable Goods (14)3.4The Short Rate and Bond Prices (16)4Separating Durable and Nondurable Consumption18 5Analysis of the General Case215.1Nondurable Consumption (21)5.2Risk Aversion (23)5.3The Behavior of K t/z t (25)5.4The Price of Durable Goods (28)5.5The Short Rate (30)5.6The Term Structure of Interest Rates (33)6Interest Rates and the Business Cycle356.1A Review of Some Empirical Findings (35)6.2The Term Spread and the Business Cycle (37)6.3The Short Rate and the Business Cycle (40)6.4The Nondurables to Durables Ratio and the Business Cycle (42)7Empirical Results427.1Data Description (43)7.2D/GNP and GNP Growth (44)7.3The Term Spread and D/GNP (47)7.4Forecasting Bond Returns (51)8Conclusion52 9Appendix559.1Lemmas5and6 (55)9.2Proof of Theorem1 (56)9.3Proof of Theorem2 (60)9.4Proof of Theorem3 (61)9.5Perturbation Analysis (61)9.6Proof of Lemma1 (63)9.7Proof of Lemma2 (64)9.8Proof of Lemma4 (64)References661IntroductionConsumption goods vary dramatically in their degrees of durability.For example,going to a movie results in relatively short-lived enjoyment,whereas purchasing a VCR will likely provide a longer lastingﬂow of service.Recognizing such distinctions,the U.S.Department of Commerce classiﬁes consumption goods as either durables or nondurables.In2000,durable and nodurable goods consumption respectively accounted for roughly12%and60%of U.S. GNP.1The asset pricing literature has long recognized that consumption patterns of investors have important implications for the prices ofﬁnancial securities(see Lucas(1978),Mer-ton(1973,1990),Cox,Ingersoll,and Ross(1985a,b),Cox and Huang(1989),and Breeden (1979)).Breeden(1979)shows that when identical investors consume a single,short lived(or nondurable)good the expected returns onﬁnancial assets depend on their covariance with the growth rate of aggregate consumption.However,subsequent empirical work has shown that this model fails to satisfactorily account for important features of the actual relation-ship between consumption and asset returns(see Hansen and Singleton(1983),Campbell (1999),and Campbell and Cochrane(2000)).Accordingly,later research has focused on ex-tending the traditional framework to incorporate more realistic assumptions about people’s preferences over consumption goods.One line of the literature considers the eﬀects of habit formation on investor behavior and on asset prices(see Constantinides(1990)and Abel(1990)).The habit formation paradigm has had some success in explaining the moments of actual returns data(see Campbell and Cochrane(1999)).Another strand of research considers utility functions where the degree of risk aversion is not linked to the elasticity of intertemporal substitution(Epstein and Zin (1989,1991)).Heaton(1993,1995)provides evidence that durability of consumption goods is important in explaining aggregate consumption data.Hindy and Huang(1993),Grossman and Laroque(1990),and Cuoco and Liu(2000)are theoretical studies of investors who consume a durable,rather than a nondurable,good.Hindy,Huang,and Zhu(1997)extend this framework to take into account habit formation over the level of durable consumption.1Based on the February28,2001Gross Domestic Product estimates available from the U.S.Department of Commerce().Durable goods consumption consists of personal consumption expenditure on durable goods plus gross private domestic investment in residential real estate.Nondurables consumption includes personal consumption expenditure on nondurables and services.Surprisingly,however,there has been relatively little work done on the asset pricing implications of investors who consume goods with diﬀerent degrees of durability.For this purpose,the ideal model is one where agents consume an arbitrary number of goods,each of which has a diﬀerent lifetime of usefulness.However,this situation is prohibitively diﬃcult to handle.To capture the qualitative aspects of the investment and consumption decision with multiple durability of goods,I will focus on investors who consume only two goods:a short lived good and a long lived good.The economy that I consider works as follows.Imagine a farmer who grows bamboo.To him,bamboo has three possible uses.First,it may be consumed for immediate satisfaction, hence its role as the nondurable good.Second,bamboo may be replanted.This will produce bamboo in the future.Third,the farmer may use bamboo to build additions to or to repair his house.The house is the durable good.Notice,however,that once bamboo has been used in the construction of the house,it will be impossible either to consume or replant it in the future.This irreversibility of investment plays an important role in the ensuing analysis. Now consider an economy that consists of many,identical such farmers.They are able to lend bamboo to one another,as well as to sell parts of their homes on a spot market(you can imagine they can sell part of a wall that another farmer may use in his own house).I will study the behavior of interest rates and of durable goods prices(or house parts prices) in this economy.In this respect,this paper is closely related to Detemple and Giannikos(1996),who consider investors who consume nondurable and durable goods.In their model agents derive “status”from their durable goods purchases.This makes the irreversibility constraint faced by these investors non-binding.In a setting similar to the one in this paper,Damgaard, Fuglsbjerg,and Munk(2000)study the control problem of an investor who consumes durables and nondurables.However they do not consider the asset pricing implications of durable and nondurable consumption.Dunn and Singleton(1986)look at an economy where agents consume durable and nondurable goods,but where durable investment is reversible.They estimate their model using U.S.bond data and reject the model as an explanation for these data.However,it is possible that the rejection is due to the fact that durable investment in their model is reversible.Finally,this paper is related to the Hindy,Huang,and Zhu(1997) paper in which investors consume a durable good and form a habit over past durable goodconsumption.In my model,consumption of the nondurable good plays the role of the habit in their model.2The contributions of this paper are both methodological and positive in nature.On the methodological side,the paper formulates and solves a general equilibrium production economy where agents care about durable and nondurable good consumption,and where durable investment is irreversible.Asset prices in this framework and an approximate closed form solution of the model are derived.On the positive side,the paper illustrates that taken together,its preference and irre-versibility assumptions eﬀect time-varying risk aversion and interest rates.This time varia-tion is not due to an exogenously speciﬁed state variable.3Instead,it is shown that the ratio of aggregate nondurable holdings to the aggregate durable goods stock(derived endogenously from optimizing behavior of agents)fully characterizes the state of the economy.The paper establishes a connection between this ratio,investment activity,andﬁnancial variables(such as interest rates and the prices of durable goods).Agents in the model are assumed to have preferences over consumption given byU(c,z)=c A z B A+Bwhere c is the instantaneous nondurable good consumption,and z is the amount of service ﬂow derived from an agent’s holdings of the durable good.Serviceﬂow from the durable is assumed to be directly proportional to the amount of durable good held.4Agents are able 2Dumas(1992)analyzes the exchange rate between two otherwise identical nondurable goods in spatially separated economies.The paper is similar to this one in that frictions exist for transfers between the capital stocks.The major diﬀerence is that both stocks in Dumas(1992)are of a nondurable consumption good. There is also an extensive and related literature on the investment decisions ofﬁrms.Kogan(2000)studies the stock prices of proﬁt maximizingﬁrms which invest in a durable good in an economy where investors’preferences over durable and nondurable consumption are additive.Other related papers include Abel and Eberly(1996),Bertola and Caballero(1994),and Dixit(1991).There has also been a considerable amount of work in macroeconomics on the interaction of investment decisions and the business cycle.Rouwenhorst (1995)provides a discussion of how this literature is relevant to topics in asset pricing.3It is well known that in the Cox,Ingersoll,and Ross(1985a,b)representative agent economy,if the production opportunity set is constant,the short term interest rate turns out to be constant as well,implying that the term structure of interest rates isﬂat.A nontrivial term structure can be obtained in this setting by assuming exogenous variation in the production opportunity set.Two prominent models of the term structure which do not need to assume exogenous state variables are Dumas(1989)and Wang(1996).Both models look at an economy with two groups of agents who have diﬀerent risk aversions inside the HARA class.Trade between these two sectors leads to endogenous variation in the short rate,and a time varying term structure of interest rates.This paper shows that endogenous variation in interest rates can be obtained by having heterogeneous consumption goods,rather than heterogeneous investors.4In fact,going forward,I will assume that the serviceﬂow is exactly equal to the durable stock.to invest their holdings of the nondurable good in a production technology with a constant investment opportunity set.Furthermore,at any time,they are able to transfer a unit of nondurable into a unit of the durable good.In order to qualitatively capture aggregate investment behavior,I assume that such transfers are irreversible.Once a unit of nondurable has been transferred into a unit of the durable good,the reverse transfer is technologically infeasible.The optimal consumption policy for the nondurable is to consume continuously at a rate c t.While the current durable stock provides a continuous serviceﬂow,new investment into the durable good occurs only periodically.Hence the economy goes through long periods of time when no new investment takes place.The implied risk aversionγof investors in this economy is given byγ≡µ−r σ2whereµandσare,respectively,the constant return and volatility of the production tech-nology,and where r is the endogenously determined short term interest rate.The above preference assumption,along with the irreversibility constraint,yield an economy where the implied risk aversion depends on the ratio of the nondurable to the durable goods.Therefore, the short term interest rate,the price of a unit of durable good,and the term structure all evolve stochastically as a function of this state variable.In the model,new investment into the durable good occurs when the short term interest rate is at its highest level.This result is in contrast to the traditional partial equilibrium analysis which suggests that new investment ought to occur when the cost of capital is lowest.The partial equilibrium analysis,however,ignores the value of new investment.The price(in units of the nondurable)of a new unit of the durable good is also highest when new investment takes place:both the numerator and the denominator of the net present value calculation are high,with the increase in the numerator being the dominant eﬀect.By not endogenizing both the cost and the beneﬁt of new investment,the traditional analysis appears to makeﬂawed predictions(see Taylor(1999)for a discussion of some relevant issues).New investment occurs when the nondurables to durables ratio is suﬃciently high.There-fore,a link can be established between this ratio andﬁnancial variables.Speciﬁcally,the term spread(the diﬀerence between a long and a short yield)is shown to be decreasing inthe nondurables to durables ratio when the economy is close to the point of new investment. The nondurables to durables ratio is shown to have a positive contemporaneous correlation with the GNP to nondurable ratio,and to have predictive power for future GNP growth. The volatility of the short rate exhibits an inverted U-shape with respect to the nondurables to durables ratio.The volatility of the durable good price has a similar behavior,and is equal to zero at the point of investment.The model provides a potential economic explanation for several empirically observed relationships between interest rates and the business cycle.For example,Fama and French (1989)document that the term spread is countercyclical,while the short rate is procyclical. Harvey(1989)ﬁnds that the term spread is able to forecast future GNP growth.Plosser and Rouwenhorst(1991)ﬁnd that the short rate also has forecasting power for growth in future output.The present model generates a term spread with a negative contemporaneous relationship with GNP,and a positive relationship with future GNP growth.Furthermore,the short rate is highest during high output periods,and is lowest during low output periods.The short rate is also shown to have predictive power for future growth in GNP.The model is therefore able to reproduce several salient features of the empirical data on interest rates and the business cycle.The underlying cause of these relationships is the irreversibility of aggregate investment in the durable good.Because of irreversibility,investment only happens after high output periods,thereby depressing the future growth rate of the productive capital (since nondurable holdings are being siphoned oﬀinto the non-growing durable stock rather than being reinvested in the production technology).This causes periods of high output to be followed by periods of low output.The present model does not admit a closed form solution,and therefore is solved numeri-cally.Also an approximate closed form solution is derived using the method of perturbation analysis.This solution is asymptotically correct as agents’preferences move towards being only concerned with nondurable good consumption.In this limit,the model becomes the standard,constant interest rate Cox,Ingersoll,Ross(1985a,b)economy.The model predicts that the ratio of GNP devoted to durable goods consumption(D/GNP) is a proxy for the nondurables to durables ratio,which is the state variable in the economy. Because new durable investment is irreversible,investors will not transfer nondurables todurables unless the nondurable stock is suﬃciently high.Hence the model predicts that D/GNP should be high following periods of high economic growth.Furthermore,the econ-omy tends to hover around the region where agents invest into the durable.This investment siphons productive capital away from the production technology,and into durable goods. Hence periods of high durable good investment ought to predict relatively low future output.A high value of D/GNP should therefore predict low output growth at some point in the future.The term spread in the model is low when new durable investment takes place.Hence D/GNP should be negatively correlated with the term spread.Also because of the persis-tence of new durable investment in the model,high durable investment should predict a low term spread in the future.Hence a high value of D/GNP should predict a low future term spread.Finally,because D/GNP should have predictive power for future term spreads,it should also have predictive power for future excess returns on long term bonds.These implications of the model are tested and conﬁrmed using U.S.GNP and govern-ment bond data for the time period from1951–1999.The D/GNP ratio is shown to be high following periods of high growth in real GNP,and to have forecasting power for future growth in real GNP.Also D/GNP is able to predict the future term spread,and to have substantial explanatory power for future excess returns on long term government bonds.These connec-tions between a pure economic variable D/GNP and the term structure suggests that the durability of consumption goods,along with the irreversibility of durable good investment, play a fundamental role in the determination of interest rates.The rest of the paper proceeds as follows.Section2formulates the model.Section3 shows how the equilibrium asset prices in this economy are derived.Section4analyzes the two base cases of the present model:consumption of only durables or only nondurables. Section5analyzes the general case of the present model.Section6analyzes the relationship betweenﬁnancial variables and real economic activity in the model.Section7presents the empirical results.Section8concludes.All proofs and the perturbation analysis are shown in the Appendix.2The ModelThe underlying uncertainty of the economy is characterized by a1dimensional standard Brownian motion B={B t:t≥0}deﬁned on itsﬁltered probability space(Ω,F,F,P). Theﬁltration F={F t:t≥0}represents the information revealed by B over time.The economy contains a nondurable good(the productive capital)and a durable good. The nondurable good acts as the numeraire.There is a production technology for the nondurable in the economy.This technology transforms units of nondurable today into units of nondurable tomorrow.Units of nondurable may also be transformed into units of the durable good.However,units of durable good may not be transformed back into the nondurable.Hence investment in the durable good is irreversible.The stock of durable good depreciates over time to reﬂect the eﬀects of physical deterioration.The aggregate nondurable stock K t and the aggregate durable stock z t evolve according todK t=µKdt+σKdB t−c t dt−dΦt(1)dz t=−θz t dt+dΦt(2)Here c t is aggregate nondurable consumption,dΦt is the time t aggregate investment into the durable,andθis the durable depreciation rate.Hereµandσare constants which characterize the production opportunities available for the nondurable goode.We assume that c t satisﬁes the appropriate integrability condition.In(1–2),the stochastic processΦt is the cumulative amount of nondurable transfered into the durable good as of time t.Investment can occur either in inﬁnitesimalﬂows or in lumps.5As will become clear,for the optimal policy,inﬁnitesimal investment occurs when 5More formally(following Hindy and Huang(1993))let us deﬁne X+as the space of all processes x with paths that are positive,increasing,and right continuous.An increasing function x(·)has aﬁnite left limit at any t,denoted by x(t−).The convention used in this paper is that x(0−)=0.A jump of x(·)atτisdenoted by∆x(τ)=x(τ)−x(τ−).We will assume thatΦt∈X+.For anyω∈Ωthe points of discontinuity ofΦ(ω,t)correspond to the times when agents transfer a non-inﬁnitesimal amount of nondurable into the durable good.The transfer processΦt has an absolutely continuous component over those times when agents transfer nondurable into the durable at a rate of dΦ(ω,t)/dt per unit time.Furthermore,Φ(ω,t)may have a singular component.The context in which the singular process arises in the present setting is the following.Let B t be a standard Brownian motion on F,and let c be some constant.Deﬁne a process A t≡sup s≤t(B s−c)+.The process A t will be singularly continuous(as opposed to absolutely continuous)and will be referred to as a singular process.Notice that(i)A t is non-decreasing and therefore ofﬁnite variation,and(ii)the controlled Brownian motion B∗t≡B t−A t will always be less than or equal to c.it is necessary to keep the pair{K t,z t}inside a region of no-investment.An inﬁnitesimal amount of nondurable will be transferred into the durable when the pair reaches the boundary of the region,and the transfer is only large enough so as to push the pair back into the region’s interior.Because the state variables in the model evolve in a continuous way,once the pair {K t,z t}is either on the boundary or inside of the no-investment region,it will remain inside this region.Lumpy investment can occur if at time0the pair{K0,z0}lies outside of the no-investment region.The lumpy control is then exerted to bring the pair to the boundary of the region.In what follows we assume,without loss of generality,that{K0,z0}is inside the no-investment region.Each unit of the durable good produces a consumption stream which is valuable to the agents in the model.Furthermore agents may consume out of their own nondurable stock. Agents’time t utility over consumption from the durable and nondurable good is given byU(c t,z t)=c A t z B tA+B,(3)where c t is the consumption rate from the nondurable,and z t is the serviceﬂow from z t units of the durable good.6It is assumed that(1)A>0,B>0and A+B<1,or(2) A<0,B<0.Agents maximize a utility of the formE0 ∞0e−ρt U(c t,z t)dt (4) The economy contains a continuum of competitive investors,all of whom have identical preferences given by(4).2.1A Pareto Optimal AllocationAll investors have identical utility functions,and start with identical ratios of nondurable to durable good holdings.That is,for every investor i,it is assumed that the ratio K i0/z i0is identical.To determine a Pareto optimal allocation in the economy,we can simply consider the control problem of a representative agent.7Agents’consumption and investment behavior depends only on their own ratios of nondurable to durable stock.If at the start of the6Alternately we can write the utility function as U(c t,z t)=1/β(cαt z1−αt)βwhereα=A/(A+B)andβ=A+B.7In the case where all investors have HARA utilities with the same risk aversion,Rubinstein(1974)showed that many such investors aggregate into a single,representative investor with the same utility function.economy,this ratio is the same for all investors,it will stay the same for all investors at all future times.Aggregation will hold regardless of the actual values of K i0.In order to characterize the equilibrium,it is suﬃcient to solve the following control problem.J(K,z,t)≡maxE0 ∞0e−ρt U(c t,z t)dt ,(5)c t,ΦtSuch that dK t=µKdt+σKdB t−c t dt−dΦt,(6)dz t=−θz t dt+dΦt,(7)K t>0z t>0dΦt≥0c t>0.(8) At the aggregate level,there is no investment in the locally riskless asset.This reﬂects the market clearing condition that all bonds are in zero net supply.We will later derive the interest rate that would induce agents to invest all of their nondurable capital in the risky production technology.The zero net supply of bonds condition will also allow us to derive the prices of bonds,and hence the term structure of interest rates,in this economy.2.2Discussion of the ModelThis model can be thought of as an extension of a simpliﬁed version of the Cox,Ingersoll, and Ross(1985a)model.In order to generate a non-trivial term structure in their model, the authors needed to assume an exogenous state variable.The obvious drawback of this approach is that an exogenously assumed source of uncertainty is diﬃcult to interpret.Another related model is Hindy and Huang(1993).They assume that agents only have utility over durable consumption.Alternatively,one can interpret the preference structure in their case as allowing for local substitution of nondurable consumption.As in Cox,Ingersoll, and Ross(1985a),the Hindy and Huang model with a constant investment opportunity set will have constant implied risk aversion,and therefore,constant interest rates.In reality,of course,people consume both durable and nondurable goods.The current model explicitly accounts for such preferences.By assuming that aggregate investment into durable goods is irreversible(how does one disinvest from a bridge,for example),the present model endogenously obtains time varying implied risk aversion.Most importantly,this is done without having to assume an exogenous state variable.The consequence of time varyingimplied risk aversion is that the short rate is stochastic,and that the term structure becomes a non-trivial function of the state of the economy.Furthermore,by assuming nothing more than the basic economic primitives,the present model has strong empirical predictions(which are discussed in Section6).Another related paper is Kogan(2000)which studies the stock price of aﬁrm engaged in irreversible real investment.The similarity obtains because the process of irreversible real investment is similar to the process of durable good investment which is studied in this paper.3The EquilibriumIn this section we will analyze the solution to the representative agent’s control problem,as well as the asset prices which obtain in equilibrium.3.1An Agent’s Control ProblemThe solution of a single agent’s problem will give us the solution to the equilibrium of the economy as long as(1)all agents have identical preferences,and(2)all agents start at time0 with identical ratios of nondurable to durable.We will assume that both of these conditions hold.The nondurable consumption in the current problem occurs at a rate c t.Investment into the durable good,however,may have a singular component.The latter problem has been studied in the literature as well.See papers by Hindy and Huang(1993),Dumas(1991), Shreve and Soner(1994)and the book by Harrison(1990),among others.The joint control of c t and the durable investment processΦt can be handled in much the same way as the control ofΦt alone.It turns out suﬃcient conditions for this problem are similar to the Bellman conditions of dynamic programming.This section will heuristically discuss the optimality conditions for the value function and control.The section concludes with the statement of a veriﬁcation theorem.A more rigorous discussion,as well as the proof of the veriﬁcation theorem,are provided in the Appendix.Let J(K t,z t,t)be the value function of a single agent.The solution of the control problem。