Alain Kabundi

THE EFFECT OF MONETARY POLICY ON HOUSE PRICE INFLATION: A FACTOR AUGMENTED VECTOR AUTOREGRESSION (FAVAR) APPROACH

Purpose - This paper seeks to assess the impact of monetary policy on house price inflation for the nine census divisions of the US economy. Design/methodology/approach - A factor-augmented VAR (FAVAR) model is estimated using a large data set comprising of 126 quarterly series over the period 1976:01 to 2005:02. Findings - Overall, the results of this investigation show that house price inflation responds negatively to a positive monetary policy shock, suggesting that the framework does not experience the widely observed price puzzle encountered while analyzing monetary policy shocks with standard sized VARs. Research limitations/implications - The paper only considers house price inflation and ignores other housing market variables. Moreover, given the recent economy-wide decline in the house price growth rates, it would be worthwhile to update the data set to a more recent period, to capture the possible breakdown in the relationship of house prices with fundamentals driving the market. Practical implications - The results based on the impulse response functions indicate that, in general, house price inflation responds negatively to monetary policy shock, but the responses are heterogeneous across the census divisions. In addition, the findings suggest, in particular, the importance of South Atlantic, East South Central, West South Central, Mountain and the Pacific divisions in shaping the dynamics of US house price inflation. Originality/value - To the best of ones knowledge, this is the first paper to analyze the effect of monetary policy on house price inflation in the nine census divisions of the US economy using a FAVAR model.

Monetary Policy and Housing Sector Dynamics in a Large-Scale Bayesian Vector Autoregressive Model

Our paper considers this channel whereby monetary policy, a Federal funds rate shock, affects the dynamics of the US housing sector. The analysis uses impulse response functions obtained from a large-scale Bayesian Vector Autoregression (LBVAR) model that incorporates 143 monthly macroeconomic variables over the period of 1986:01 to 2003:12, including 21 variables relating to the housing sector at the national and four census regions. We find at the national level that housing starts, housing permits, and housing sales fall in response to the tightening of monetary policy. Housing sales reacts more quickly and sharply than starts and permits and exhibits more duration. Housing prices show the weakest response to the monetary policy shock. At the regional level, we conclude that the housing sector in the South drives the national data. The responses in the West differ the most from the other regions, especially for the impulse responses of housing starts and permits.

Three Cycles: Housing, Credit, and Real Activity

We examine the characteristics and comovement of cycles in house prices, credit, real activity and interest rates in advanced economies during the past 25 years, using a dynamic generalised factor model. House price cycles generally lead credit and business cycles over the long term, while in the short to medium run the relationship varies across countries. Interest rates tend to lag other cycles at all time horizons. While global factors are important, the U.S. business cycle, house price cycle and interest rate cycle tend to lead the respective cycles in other countries over all time horizons. However, the U.S. credit cycle leads mostly over the long term.

Estimation of Economic Growth in France Using Business Survey Data

This paper proposes a new way of computing a coincident indicator for economic activity in France using data from business surveys. We use the generalized dynamic factor model a la Forni and others (2000) to extract common components from a large number of survey observations. The results obtained show that the resulting indicator forecasts economic activity with a relatively high degree of accuracy before the release of actual data.

THE EFFECT OF DEFENSE SPENDING ON US OUTPUT: A FACTOR AUGMENTED VECTOR AUTOREGRESSION (FAVAR) APPROACH

Empirical evidence on the effect of defense spending on US output is at best mixed. Against this backdrop, this paper assesses the impact of a positive defense spending shock on the growth rate of real GNP using a Factor Augmented Vector Autoregressive (FAVAR) model estimated with 116 variables spanning the quarterly period of 1976:01 to 2005:02. Overall, the results show that a positive shock to the growth rate of the real defense spending translates to a positive short‐run effect on the growth rate of real GNP lasting up to ten quarters, but the effect is significant only for two quarters. Beyond the tenth quarter, the effect becomes negative and shows signs of slow reversal at around the 17th quarter. Our results tend to indicate that the mixed empirical evidence, based on small‐scale Vector Autoregressive (VAR) and Vector Error Correction (VEC) models, could be a result of a small information set not capturing the true theoretical relationships between the two variables of interest.

Recent French Export Performance; Is There a Competitiveness Problem?

Recently, the export performance of France relative to its own past and relative to a major trading partner, Germany, deteriorated. That deterioration seems related to the geographical destination and product composition of trend exports. Faced with an increase in unit labor costs or in its terms of trade, France adjusts relatively less via price and wage changes, and more via employment changes. Given that SMIC convergence resulted in a significant increase in unit labor costs, foreign sector difficulties might be structural. Trade flows relevance and euro area policy constraints highlight the importance of structural reforms that increase markets flexibility.

Using large data sets to forecast sectoral employment

We use several models using classical and Bayesian methods to forecast employment for eight sectors of the US economy. In addition to using standard vector-autoregressive and Bayesian vector autoregressive models, we also augment these models to include the information content of 143 additional monthly series in some models. Several approaches exist for incorporating information from a large number of series. We consider two multivariate approaches—extracting common factors (principal components) and Bayesian shrinkage. After extracting the common factors, we use Bayesian factor-augmented vector autoregressive and vector error-correction models, as well as Bayesian shrinkage in a large-scale Bayesian vector autoregressive models. For an in-sample period of January 1972 to December 1989 and an out-of-sample period of January 1990 to March 2010, we compare the forecast performance of the alternative models. More specifically, we perform ex-post and ex-ante out-of-sample forecasts from January 1990 through March 2009 and from April 2009 through March 2010, respectively. We find that factor augmented models, especially error-correction versions, generally prove the best in out-of-sample forecast performance, implying that in addition to macroeconomic variables, incorporating long-run relationships along with short-run dynamics play an important role in forecasting employment. Forecast combination models, however, based on the simple average forecasts of the various models used, outperform the best performing individual models for six of the eight sectoral employment series.

Business cycle co-movements between South Africa and the BRIC countries

This article examines the relationships between South African economy and the economies of the BRIC (Brazil, Russia, India and China). In particular, it identifies the nature and key features of the co-movement of South African business cycles with cycles of the BRIC countries. It uses the dynamic factor model to a set of 307 macroeconomic series during the period 1995Q2 to 2009Q4. We found significant evidence of synchronization between South Africa and the BRIC countries over the business cycle, although the magnitude of co-movement differs with each country. India portrays strong ties with South Africa over time. Moreover, Brazil, China and Russia lead South Africa in the long run, while India is contemporaneous. Further, the findings imply that the first two factors are BRICS factors while the third one is a US factor.

Monetary Policy and Balance Sheets

This paper evaluates the strength of the balance sheet channel in the U.S. monetary policy transmission mechanism over the past three decades. Using a Factor-Augmented Vector Autoregression model on an expanded data set, including sectoral balance sheet variables, we show that the balance sheets of various economic agents act as important links in the monetary policy transmission mechanism. Balance sheets of financial intermediaries, such as commercial banks, asset-backed-security issuers and, to a lesser extent, security brokers and dealers, shrink in response to monetary tightening, while money market fund assets grow. The balance sheet effects are comparable in magnitude to the traditional interest rate channel. However, their economic significance in the run-up to the recent financial crisis was small. Large increases in interest rates would have been needed to avert a rapid rise of house prices and an unsustainable expansion of mortgage credit, suggesting an important role for macroprudential policies.