货币政策对房地产泡沫的影响研究——基于vecm模型的实证分析外文翻译资料

Monetary Policy and the Housing Bubble

1 Introduction

There is general agreement that the bursting of the housing price bubble in the US set off the severe financial crisis and deep recession of 2007–2009. Most observers were surprised by the fragility of the financial system and the resulting depth of the crisis that was initiated by the collapse of one sector of the financial system, the secondary home mortgage market. The literature on this episode is expanding rapidly, but more empirical research is needed. The purpose of this paper is to conduct an empirical test of the effect of monetary policy on an index of housing prices to determine the extent to which monetary policy produced the housing price bubble. Many observers blame the interest rate policy of the Federal Reserve Bank during the critical years of 2001–2004. Other observers do not place the Fed’s interest rate policy at the center of the story.

The Financial Crisis Inquiry Commission (2011) observed that the Federal Reserve began lowering the federal funds rate from 6.60% in early 2001, and this rate reached a low point of 1.0% in August, 2003. The Commission (p. 85) states that：Low rates cut the cost of homeownership: interest rates for the typical 30-year fixed-rate mortgage traditionally moved with the overnight fed funds rate, and from 2000 to 2003, this relationship held. By 2003, creditworthy home buyers could get fixed-rate mortgages for 5.2%, 3 percentage points lower than 3 years earlier. The savings were immediate and large.

This study examines the possible influence of the federal funds rate on the Samp;P/ Case-Shiller Housing Price Indices using time-series methods. Monthly data from January, 1987 to August, 2010 are used. The basic finding is that Granger causality exists running from the federal funds rate to the housing price index, and that the effect is much stronger in the period beginning in the year 2000. This empirical method was employed by Bernanke and Blinder (1992) to investigate the channels of transmission of monetary policy. They found (1992) that” according to the Granger-causality criterion, the federal funds rate is far and away the best predictive variable (of macroeconomic variables) among the five considered.”1 Also Bernanke and Blinder (1992) used innovations in the federal funds rate as a measure of changes in policy, and found evidence that monetary policy partly operates through the supply of bank credit. After first discussing the theoretical issues, data are discussed, the model is developed, and the results are presented.

2 The Data

This study makes use of two time-series data sets, the federal funds rate in the market, and the Samp;P/Case-Shiller Home Price Indices (2010). The Samp;P/Case-Shiller Home Price Indices for single-family home prices are generated and published monthly, and include 10 and 20 metropolitan area composite indices and indices for possible physical changes in the house. This study makes use of the composite indices for both the 10 and the 20 metropolitan areas and the individual indices for the 20 metropolitan areas.

3 Model Estimation, Discussion, and Testing

As discussed in the prior section, there is substantial controversy over whether the Federal Reserve policy regarding the federal funds rate had an impact on the pattern of housing prices. Those arguing in favor of an effect stress that the reduction in the Fed Funds rate to 1% in 2003, and subsequently holding it down for a couple of years, “caused” the housing price bubble.

Given that = the composite housing price index in period t and = the federal funds rate, will Granger (1969) cause if a model

（3-1）

An alternative way to proceed that includes the possibility of feedback from y to x is to use a VAR model of the form

（3-2）

which can be written as

（3-3）

where Granger causality from x to y implies that where is a polynomial in the lag operator B with m terms. Zellner and Palm (1974) have a detailed discussion of the relationship between these alternatives models, both of which have their uses. For example Eq. 1 can be written

（3-4）

which can be simplified to

（3-5）

4 Results

Using the data of this paper, m was set as 12 so as to remove all significant autocorrelations and cross correlations in the estimated VAR residuals. Granger causality tests using this setup are listed in Table 4-1. Logs of both the interest rate series and housing series are used. Model 3-1 reports results in the period 2000–2010/8 using the 10 city housing price series and finds the log of the federal funds rate significantly (.996985) Granger-causes the housing series. Model 3-2 removes 12 observations for 1999 to be compatible with that which can be obtained in model 3-6 with the 20 city composite series that is only available starting with 2000/1, and again finds the log of the federal funds rate significantly (.997648) Granger-causes the log housing series. Here the significance is .995032. The above findings suggest that in the 2000–2010/8 period the log federal funds rate Granger-causes the housing series.

Table 4-1 Granger causality tests of LNFFRATE