1,721,011 research outputs found
Interest Rate Modeling and Forecasting in India
Get PDFThe 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.
Predicting Indian Business Cycles: Leading Indices for External and Domestic Sectors
No full textThis 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.business cycle, economic cycle, growth rate, leading index of Indian exports, export performance, Economics
Analysis of Consumers’ Perceptions of Buying Conditions for Houses
No full textConsumers’ buying attitudes, Survey data, Cointegration, Generalized impulse responses and variance decompositions,
Analysis of Consumers' Perceptions of Buying Conditions for Houses
Get PDFThis 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.
Interest Rate Modeling and Forecasting in India
No full textThe interest rate is a key financial variable that affects decision of consumers, businesses, financial institutions, professional investors and policymakers. Timely forecast of interest rates can therefore provide valuable information to financial market participants and policymakers. The objective of this study is to develop models to forecast short term and long term rates. The study develops univariate and multivariate models to forecast these rates.univariat, multivariate, interest rates, forecast of interest rate, reserve bank
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Modelling and Forecasting Seasonality in Indian Macroeconomic Time Series
No full textThis paper models the univariate dynamics of seasonally unadjusted quarterly macroeconomic time series for the Indian economy including industrial production, money supply (broad and narrow measures) and consumer price index. The seasonal integration-cointegration and the periodic models are employed. The ‘best’ model is selected on the basis of a battery of econometric tests including comparison of out-of sample forecast performance. [Working Paper No. 136]Seasonality, Integration, Periodic Integration, Forecast Performance
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