Analysis of Consumers' Perceptions of Buying Conditions for Houses

This paper examines the determinants of consumers' buying attitudes for houses. Data on buying attitudes are from responses to the Surveys of Consumer Attitudes conducted by the Survey Research Center, University of Michigan. The determinants considered include current and expected interest rates, current and expected real disposable income and house prices. The empirical estimates show that a long-run relationship exists between buying attitudes for houses and each of the above variables. Each of these determinants also Granger cause buying perceptions. Generalized impulse responses show that shocks to each of the above variables have a predictable and permanent impact on buying attitudes. Furthermore, generalized variance decompositions suggest that both current and expected interest rates explain a large proportion of the variation in consumers’ perceptions towards buying houses. Since consumers' attitudes towards buying houses are likely to be translated into actual purchases, this study shows that in order of importance, interest rates - both current and future - have the maximum impact on decisions to purchase houses followed by expectations of real disposable income.Consumer Surveys, House Buying Attitudes, Cointegration, Generalized Variance Decompositions, Impulse Responses.

Business Cycles in India

This paper describes business and growth rate cycles with special reference to the Indian economy. It uses the classical NBER approach to determine the timing of recessions and expansions in the Indian economy, as well as the chronology of growth rate cycles, viz., the timing of speedups and slowdowns in economic growth. The reference chronology for business as well as growth rate cycles is determined on the basis of the consensus of key coincident indicators of the Indian economy, along with a composite coincident index comprised of those indicators, which tracks fluctuations in current economic activity. Finally, it describes the performance of the leading index – a composite index of leading economic indicators, designed to anticipate business cycle and growth rate cycle upturns and downturns.business cycles; growth rate cycles; coincident index; leading index, Indian economy

Predicting Indian Business Cycles-- Leading Indices for External and Domestic Sectors

This paper evaluates the real-time performance of the growth rate of the DSE-ECRI Indian leading index for exports for predicting cyclical downturns and upturns in the growth rate of Indian exports. The index comprises the 36-country real effective exchange rate and leading indices of India’s 17 major trading partners. Leading indices of India’s major trading partners were developed at the Economic Cycle Research Institute and forecast the onset and end of recessions in overall economic activity in these economies. The results show that the real-time performance of the growth rate of the leading index of Indian exports has been creditable in the last seven years since its construction in 2001. In conjunction with the DSE-ECRI Indian Leading Index, designed to monitor the domestic economy, the exports leading index forms a sound foundation for a pioneering effort to monitor Indian economic cycles.

East Asian Crisis and Currency Pressure: The Case of India

This paper tests and explains the impact of the East Asian crisis on India’s exchange rate. To examine this, an index of currency pressure is estimated for four countries -- Thailand, South Korea, Malaysia and India covering the period just before, during and after the crisis. A contagion model with panel data for these four countries is also estimated during the crisis period. On the basis of the panel data estimates, the paper concludes that while India experienced some effects of the crisis, these were not substantive. This is partly attributed to the role of stabilisation policy in India that included intervention in the foreign exchange market by the central bank, phased tightening of monetary policy and restrictions on capital flows.

CAPITAL FLOW VOLATILITY AND EXCHANGE RATES-- THE CASE OF INDIA

This paper examines the relationship between the real exchange rate, level of capital flows, volatility of the flows, fiscal and monetary policy indicators and the current account surplus for the Indian economy for the period 1993Q2 to 2004Q1. The estimations indicate that the variables are cointegrated and each granger causes the real exchange rate. The generalized variance decompositions show that determinants of the real exchange rate, in descending order of importance include net capital inflows and their volatility (jointly), government expenditure, current account surplus and the money supply. A preliminary analysis suggests that a similar analysis can be performed for the foreign exchange reserves held by the RBI.real exchange rate, capital flows, foreign exchange reserves, cointegration,

Modelling and Forecasting the Indian Re/US Dollar Exchange Rate

This paper develops vector autoregressive and Bayesian vector autoregressive models to forecast the Indian Re/US dollar exchange rate which is governed by a managed floating exchange rate regime. It considers extensions of the monetary model that include the forward premium, capital inflows, volatility of capital flows, order flows and central bank intervention. The study finds that the monetary model generally outperforms the naïve model. It also finds that forecast accuracy can be improved by extending the monetary model to include forward premium, volatility of capital inflows and order flow. Information on intervention by the central bank also helps to improve forecasts at the longer end. The study also reports that the Bayesian vector autoregressive models generally outperform their corresponding VAR variants.exchange rate; monetary model; VAR and Bayesian VAR models

Interest Rate Modeling and Forecasting in India

The study develops univariate (ARIMA and ARCH/GARCH) and multivariate models (VAR, VECM and Bayesian VAR) to forecast short- and long-term rates, viz., call money rate, 15-91 days Treasury Bill rates and interest rates on Government securities with (residual) maturities of one year, five years and ten years. Multivariate models consider factors such as liquidity, Bank Rate, repo rate, yield spread, inflation, credit, foreign interest rates and forward premium. The study finds that multivariate models generally outperform univariate ones over longer forecast horizons. Overall, the study concludes that the forecasting performance of Bayesian VAR models is satisfactory for most interest rates and their superiority in performance is marked at longer forecast horizons.

Determinants of Weekly Yields on Government Securities in India

This paper examines the determinants of the Government yields in India using weekly data from April 2001 through March 2009. The analysis covers Treasury Bills with residual maturity of 15-91 days and Government securities of residual maturity one, five and ten years respectively. The empirical estimates show that a long-run relationship exists between each of these interest rates and the policy rate, rate of growth of money supply, inflation, interest rate spread, foreign interest rate and forward premium. At the same time, the empirical results also show that the relative importance of the determinants varies across the maturity spectrum. The normalized generalized variance decompositions suggest that the policy rate and the rate of growth of high powered money are less important in explaining the proportion of variation in longer term interest rates. The weight of the forward premium also diminishes as we move towards higher maturity interest rates. The inflation rate is also relatively less important in explaining variations in the 10-year rate. The yield spread, on the other hand, is more important in explaining the longer term rates. The results also show that a large proportion of the variation in the rates on the 5-year and 10-year government securities is attributed to the interest rate itself suggesting that the unexplained variation may be a result of cyclical factors that are relatively more important for longer term rates but are not captured by the yield spread and are omitted from the estimations due to the high frequency of data employed.interest rate determination; government yields; cointegration and generalized variance decompositions

Performance Evaluation of the New Connecticut Leading Employment Index Using Lead Profiles and BVAR Models.

Dua and Miller (1996) created leading and coincident employment indexes for the state of Connecticut, following Moore's (1981) work at the national level. The performance of the Dua-Miller indexes following the recession of the early 1990s fell short of expectations. This paper performs two tasks. First, it describes the process of revising the Connecticut Coincident and Leading Employment Indexes. Second, it analyzes the statistical properties and performance of the new indexes by comparing the lead profiles of the new and old indexes as well as their out-of-sample forecasting performance, using the Bayesian Vector Autoregressive (BVAR) method. The new coincident index shows improved performance in dating employment cycle chronologies. The lead profile test demonstrates that superiority in a rigorous, non-parametric statistic fashion. The mixed evidence on the BVAR forecasting experiments illustrates the truth in the Granger and Newbold (1986) caution that leading indexes properly predict cycle turning points and do not necessarily provide accurate forecasts except at turning points, a view that our results support.Business cycles, leading and coincident employment indexes, turning points, BVAR Models

SYNCHRONIZATION OF RECESSIONS IN MAJOR DEVELOPED AND EMERGING ECONOMIES

This paper examines various measures of synchronization of recessions, including clustering of the onset of recession across economies, proportion of economies in expansion and the diffusion index of international coincident indexes, and shows that the recent global recession was possibly the most concerted in the post world war period. Factors that contributed to the synchronization and severity of the recession, such as trade and financial linkages and timing of policy actions, are analysed.