外文翻译--货币政策效应的区域差异模式

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1、中文 3380 字， 1930 单词 出处 : Crone T M. A pattern of regional differences in the effects of monetary policyJ. Business Review, 2007 (Q3): 9-19. 作者 : Theodore M.Crone 原文 : A Pattern of Regional Differences in the Effects of Monetary Policy . Introduction Although there is only one national monetary policy

2、, that does not mean that monetary policy does not affect some regions oi the country more than others. We know that business cycles differ across states and regions, and a number of studies have examined how monetary policy may affect regions differently and why. A review of these studies reveals t

3、hat certain parts of the country are consistently more affected by monetary policy than others.Identifying the reasons for regional differences in the effects of monetary policy may help us better understand how changes in monetary policy ripple through the economy. In this article, Ted Crone review

4、s where the research has brought us so far Federal Reserve officials are sometimes asked how monetary policy can help solve regional economic problems. The standard answer is straightforward； There is only one national monetary policy, and it is no designed to address purely regional issues. This do

5、es not mean, however,that monetary policy does not affect some regions of the country more than others. Business people, civic leaders,and government officials may want to know how much their region will be affected by changes in monetary policy relative to the rest of the country.We know that busin

6、ess cycles differ across states and regions, and over the past decade, a number of studies have examined what role monetary policy may play ? i.e, how monetary policy may affect regions differently and why. A review of these studies reveals that certain parts of the country are consistently more aff

7、ected by mon- etary policy than others. So far, the only convincing explanation for these differences is the different mix of industties in the regions. But the search for other reasons is likely to continue.consistently more affected by monetary policy than others. So far, the only convincing expla

8、nation for these differences is the different mix of industries in the regions.But the search for other reasons is likely to continue.Identifying the reasons for regional differences in the effects of monetary policy may help us better understand how changes in monetary policy ripple through the eco

9、nomy. This article will review where the research has brought us so far. . BUSINESS CYCLES DIEFER ACROSS STATES AND REGIONS It is widely recognised that there are differences in business cycles across states. In some cases, it is the depths of the recessions, and in others, it is the timing of reces

10、sions. Differences in cycles across multi-state regions in the U.S. are less pronounced than differences across individual states, but they are still discernible Two recent studies have used a newly developed set of coincident indexes for the 50 states to define and compare state recessions. In an e

11、arlier Business Review article, I used these indexes to examine recessions at the state level based on the traditional definition of a recession ?a significant decline in economic activity that lasts for several months. Using the same set of indexes, in a second study, economists at the St. Louis Fe

12、d applied a standard technique, known as a Markov switching model, to identify different phases in each states economic cycle. Both articles find that the 50 states have experienced different business cycles in terms of their number,timing, and severity Other studies have examined the issue from a d

13、ifferent perspective. How closely are the cyclical movements in income or employment correlated across the states? In a study published in 2001, Christophe Croux and his coauthors proposed a new statistic, called a cohesion index, which measures the co-movement of regional economies over the husines

14、s cycle. They apply the measure to personal income in the 50 states and find that while the correspondence among the states is higher than the correspondence among the European countries, it is not perfect.In a 2004 article, Gerald Carlino and Robert DeFina calculate the same statistic for employmen

15、t in eight major industry groups across 38 states for which data are availahle. A value of one would indicate a perfect correlation of industry employment by state across business cycles. Thus, for an industry with a cohesion index of one,quarterly increases and decreases in employment due to the bu

16、siness cycle would be proportional across all the states. The cohesion measures in the study range from 0.82 for manufacturing to 0.44 for mining. Thus, business cycles for the major industries differ across tbe states. The co-movement of income or employment among multistate regions is stronger tha

17、n the co-movement among the states, hut again,it is not perfect. In effect, grouping states together smooths out some of the individual features of business cycles, but it does not eliminate them Since husiness cycles differ across states and across regions in tbeU.S.,it is natural to ask whether di

18、fferential effects of monetary policy are a factor. Answering this question requires a consistent framework to measure the effect of monetary policy on the economies of states or regions. . ESTIMATING THE REGIONAL EFFECTS OF MONETARY POLICY In recent years economists have turned to econometric model

19、s known as vector autoregression VAR models to measure tbe effects of changes in monetary policy on states and regions.A VAR is a system of equations for estimating the historical relationship between a variable, sucb as personal income in a region, hy past values of that variable and by current and

20、 past values of other variables, such as the short-term interest rate targeted by the Federal Reserve the fed funds rate.Using this type of model, we can estimate the effect of an unanticipated change in the fed funds rate on income in a state or region. These effects are known as impulse responses.

21、 Of course, the estimates will differ depending on what variables are included in tbe model and what assumptions are made. For example, do changes in monetary policy affect income in the current period or only in later periods? And do shocks to one regions economy spill over directly to the economie

22、s of other regions The recent studies differ somewhat in tbeir assumptions. But all of the studies include in tbeir models three key variables: personal income in each region, the fed funds rate, and some measure ot oil prices or commodity prices in general. Some of the models add other variables to

23、 this list, such as the rate on 10-year Treasury bills. In each study, the regional effects of monetary policy are measured by the response over time of the regions personal Income to an unanticipated change in the ted funds rate. All of the models assume that unanticipated changes in the fed funds

24、rate affect personal income with a lag of at least one quarter Ideally, we would like to estimate the effects of monetary policy on each of the 50 states in a single model. But VAR models are suitable only for a limited number of variables, not the 50 plus variables tbat would be required to include

25、 each of tbe states in the same model. Therefore, the differential effects of monetary policy have generally been estimated by region rather than by state. And most of the studies use the eight regions defined by the Bureau ot Economic Analysis BEA. . The Earliest Model About 10 years ago in the Bus

26、iness Review, Gerald Carlino and Robert DeFina published the tirstottbe recent articles that used a VAR model to estimate the regional effects of monetary policy. They assume that monetary policymakers can react to a shock or unanticipated change in a regions personal income growth in the same quart

27、er.Personal income, however, responds to changes in monetary policy only in subsequent quarters because monetary policy affects tbe economy only after some time lag. The authors also assume that any change to personal income in one region can spill over to other regions in subsequent periods. Thtis,

28、 there can be a tipple effect across regions On the basis of these assumptions, Carlino and DeFina estimate the cumulative response of real personal income growth in each of the eight BEA regions to an unanticipated increase in the federal funds rate. The maximum effect in each region of an unantici

29、pated change in the federal funds rate occurs after two to two-and-a-half years. In three of the eight BEA regions, the cumulative effect is significantly diffetent from the national average after a few quarters and remains significantly different through 20 quarters. Figure 1 shows the cumulative r

30、esponses for these three regions. In the Great Lakes region, the effect of changes in monetary policy on personal income is significantly greater than the national average. In the Southwest and Rocky Mountain regions, the effect is significantly less than the national average. This pattern reoccurs

31、to some extent in most other studies of the regional effects of monetary policy In a recent study on grouping states into regions, I found additional support for Carlino and DeFinas findings. In the 1950s the BEA grouped contiguous states into eight regions based on a number of economic and social c

32、haracteristics at that time. But there was no attempt to ensure that states in the same region had similar business cycles, an important consideration for analyzing regional business cycles. I grouped contiguous states into regions based on how closely their economies moved together over the busines

33、s cycle See Alternative Definitions of Regions in the U.S. It turns out that over the past quarter century, the business cycles in some states were more closely aligned with those in states in neighboring BEA regions than those in their own region. Although the realignment of states into different r

34、egions was based on a purely statistical measure of the similarity in business cycles, some of the realignment was obvious. For example, most observers would not question that the oil-rich economy of Louisiana, which is in che BEAs Southeast region, is much closer to that of Texas and Oklahoma,which

35、 are in the BEAs Southwest region, than to the economies of the other states in che Southeast region Using this alternative definition of regions, I replicated CarUno and DeFinas original scudy. The same basic patcerns emerged as in the original study, but the results were stronger.The effects of mo

36、netary policy were significantly different from the national average in more regions than in the original study Figure 2. The impulse responses were more precisely estimated for the alternative regions than tor the BEA regions. The states around the Great Lakes formed the most significantly affected

37、 region just as in che original study. But the West was also affected more significantly than the U.S. average. The Energy Belt was the least affected region in the replication. This region contains six of the nine states in the BEAs Southwest and Rocky Mountain regions ?the least affected regions in Carlino and DeFinas study. The Mideast was also less affected than the national average in my replication of Carlino and DeFinas study. . SUMMARY