Dynamics of family size and composition: a computer simulation study with reference to rural India

"This study attempts to understand the dynamics that produce the persistent observation of a strong positive correlation between family size and extent of landholdings in predominantly agrarian economies [in India]. Such a correlation can arise from different types of demographic configurations including the rules of family formation. For example, big landholdings may be associated with large families, despite the lack of differentials across holdings of different size in fertility and mortality, simply because these families may remain undivided for long periods. In the absence of conclusive data to analyse this relationship in the Indian case, this study sets up a computer simulation model for studying the results of alternative demographic configurations."     

Presidential Elections and the Stock Market: Comparing Markov-Switching and Fractionally Integrated GARCH Models of Volatility

Bumba Mukherjee Department of Political Science, Florida State University, 554 Bellamy Building, Tallahassee, FL 32306 e-mail: smukherj{at}mailer.fsu.edu Existing research on electoral politics and financial marketspredicts that when investors expect left parties—Democrats(US), Labor (UK)—to win elections, market volatility increases.In addition, current econometric research on stock market volatilitysuggests that Markov-switching models provide more accuratevolatility forecasts and fit stock price volatility data betterthan linear or nonlinear GARCH (generalized autoregressive conditionalheteroskedasticity) models. Contrary to the existing literature,we argue here that when traders anticipate that the Democraticcandidate will win the presidential election, stock market volatilitydecreases. Using two data sets from the 2000 U.S. presidentialelection, we test our claim by estimating several GARCH, exponentialGARCH (EGARCH), fractionally integrated exponential GARCH (FIEGARCH),and Markov-switching models. We also conduct extensive forecastingtests—including RMSE and MAE statistics as well as realizedvolatility regressions—to evaluate these competing statisticalmodels. Results from forecasting tests show, in contrast toprevailing claims, that GARCH and EGARCH models provide substantiallymore accurate forecasts than the Markov-switching models. Estimatesfrom all the statistical models support our key prediction thatstock market volatility decreases when traders anticipate aDemocratic victory.     

Finding Friends

An expatriate life has a certain thrill to it-a new country, a new culture, the exploits and escapades-but it is the interaction with the people that we carry with us on our last flight back home.My China sojourn began in the summer of 1999-September 20 to be exact. It was supposed to last a couple of months, and as it happens to many of us,I ended up staying longer than I had planned to.