Data Revisions in India and its Implications for Monetary Policy

This paper studies data revision properties of GDP growth and inflation as measured by the Wholesale Price Index (WPI) for the Indian economy. We find that data revisions to GDP growth and WPI inflation in India are significant. The results show that revisions to GDP growth and WPI inflation can not be characterized as either containing pure news or pure noise. We also find that there is a significant predictable component in revisions to GDP growth and inflation. Our findings suggest that if the Reserve Bank of India were to follow a Taylor rule for its monetary policy formulation, then the interest rate based on the preliminary data would be much lower than the one based on the fully revised data.Data Revisions, Real-Time Data, Monetary Policy

Modeling Inflation in India: The Role of Money

This paper studies the role of the real money gap- the deviation of real money balance from its long-run equilibrium level- for predicting inflation in India. Using quarterly data on manufacturing inflation from 1982 to 2007, we find that the real money gap is a significant predictor of inflation in India. Our results show that this variable is a better predictor of future inflation at quarterly horizon than the deviation of broad money growth from its target for the whole sample period. We also document a break in the overall predictability of inflation in the last quarter of 1995. We find that except for the real money gap, the forecasting power of other predictors under study has declined considerably after 1995.Inflation. Monetary Policy, Indian Economy

The Instability in the Monetary Policy Reaction Function and the Estimation of Monetary Policy Shocks

This paper uses the conventional wisdom about the shift in the monetary policy stance in 1979 to compute monetary policy shocks by estimating different monetary policy reaction functions for the pre-1979 and post-1979 time periods. We use the information from the internal forecasts of the Federal Reserve to derive monetary policy shocks. The results in this paper show that a monetary policy shock in the pre-1979 period affects output and prices much more strongly and quickly than what has been reported in the literature for the full sample. Our findings suggest that the dynamic response of output and prices to a monetary policy shock declined significantly between 1980-2001. We argue that this diminished response to the monetary policy shock is the result of a successful monetary policy that has led to a less volatile economy.Monetary Policy Shocks, Greenbook data, Reaction Function

Is the East African Community an Optimum Currency Area?

This paper investigates whether the East African Community (EAC) constitutes an optimum currency area (OCA) by estimating the degree and evolution of business cycle synchronization between the EAC countries. We also investigate whether the degree of business cycle synchronization has improved after signing of the EAC treaty in 1999. The degree of business cycle synchronization is estimated using an unobserved components model of structural shocks obtained from a structural VAR model. We then use a time-varying parameter model to estimate the evolution of business cycle synchronization. Our results indicate that the proportion of shocks that is common across different countries is small, implying weak synchronization. However, we also find that the degree of synchronization has improved after signing of the EAC treaty in 1999.East African Community, Optimum Currency Area, Business Cycle Synchronization, Structural VAR, State-Space Model

VAR estimation and forecasting when data are subject to revision

Conventional VAR estimation and forecasting ignores the fact that economic data are often subject to revision many months or years after their initial release. This paper shows how VAR analysis can be modified to account for such revisions. The proposed approach assumes that government statistical releases are efficient with a finite lag. It takes no stand on whether earlier revisions are “noise” or “news.” The technique is illustrated using data on employment and the unemployment rate, real GDP and the unemployment rate, and real GDP and the GDP/consumption ratio. In each case, the proposed procedure outperforms conventional VAR analysis and the more-restrictive methods for handling the data-revision problem that are found in the existing literature.

The Superiority of Greenbook Forecasts and the Role of Recessions

In this paper, we investigate the role of recessions on the relative forecasting performance of the Fed and the private sector. Romer and Romer (2000) showed that the Fed's forecasts of inflation and output were superior to that of the private sector in the pre-1991 period. D'Agostino and Whelan (2008) found that the information superiority of the Fed deteriorated after 1991. Our results show that the information superiority of the Fed in forecasting real activity did arise from its forecasting dominance during recessions. If recessions are excluded from the pre-1992 period, the informational advantage of the Fed disappears, and in some cases, private sector forecasts perform better. We do not find any systematic effect of recessions on inflation forecasts.Greenbook Forecasts, Recessions, Business Cycle Turning Points

Understanding the Relationship between Public and Private Commercial Real Estate Markets

This paper studies the dynamic relationship between public and private commercial real estate market in the U.S. To do so, we propose a correlatedcunobserved component model with a common trend and Markov-Switching heteroscedasticity. This model addresses the dichotomy in the relationship between these two markets in the short-run and the long-run by allowing for a common long-run trend and correlated short-run cycles. To take into account the non-linearity in the commercial real estate dynamics, we also allow Markov regime-switching in shocks to the trend and the cycles. Consistent with the findings of the literature, we find almost one-for-one comovement in these two markets in the long-run. However, our results suggest significant difference in the correlation of the cycles in low volatility and high volatility regimes. We find high degree of correlation between private and public commercial real estate cycles only in the high volatility regime. This explains the low correlation in the return of these two markets as has been widely reported in the literature. Moreover, we also find that the past movements in public commercial real estate cycle predict future movement in private commercial real estate cycles reflecting the forward-looking nature of the public commercial real estate market

Forecasting House Prices: The Role of Fundamentals, Credit Conditions, and Supply Indicators

This paper evaluates the ability of various indicators related to macroeconomic fundamentals, credit conditions, and housing supply to predict house price growth in the United States during the post-financial crisis period. We find that the inclusion of different measures of housing supply indicators significantly improves the forecasting performance for the period of 2010-2022. Specifically, incorporating the monthly supply of new homes into a VAR model with house price growth reduces the RMSE by over 30 percent compared to a univariate benchmark. Moreover, forecasting accuracy improves further at a longer forecast horizon (greater than three months) when the mortgage rate spread is also used as a predictor. Further improvements are made if "Direct" forecasts are used instead of iterative forecasts. The shrinkage method like LASSO shows that the monthly supply of new homes is an important predictor at all forecasting horizons, while the mortgage spread is most relevant for longer forecast horizons

Modeling Inflation in India: The Role of Money

This paper studies the role of the real money gap- the deviation of real money balance from its long-run equilibrium level- for predicting inflation in India. Using quarterly data on manufacturing inflation from 1982 to 2007, we find that the real money gap is a significant predictor of inflation in India. Our results show that this variable is a better predictor of future inflation at quarterly horizon than the deviation of broad money growth from its target for the whole sample period. We also document a break in the overall predictability of inflation in the last quarter of 1995. We find that except for the real money gap, the forecasting power of other predictors under study has declined considerably after 1995

Data Revisions in India and its Implications for Monetary Policy

This paper studies data revision properties of GDP growth and inflation as measured by the Wholesale Price Index (WPI) for the Indian economy. We find that data revisions to GDP growth and WPI inflation in India are significant. The results show that revisions to GDP growth and WPI inflation can not be characterized as either containing pure news or pure noise. We also find that there is a significant predictable component in revisions to GDP growth and inflation. Our findings suggest that if the Reserve Bank of India were to follow a Taylor rule for its monetary policy formulation, then the interest rate based on the preliminary data would be much lower than the one based on the fully revised data