Bahram Pesaran and M. Hashem Pesaran. “Conditional Volatility and Correlations of Weekly Returns and the VaR Analysis of 2008 Stock Market Crash”, Special Issue of Economic Modelling in honour of PAVB Swamy, edited by Stephen G. Hall, Lawrence R. Klein, George S. Tavlas and Arnold Zellner, 27, 1398-1416, 2011
Abstract: Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated during the recent financial crisis. We shall examine the nature of asset return correlations using weekly returns on futures markets and investigate the extent to which multivariate volatility models proposed in the literature can be used to formally characterize and quantify market risk. In particular, we ask how adequate these models are for modelling market risk at times of financial crisis. In doing so we consider a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and show that the t-DCC model passes the usual diagnostic tests based on probability integral transforms, but fails the value at risk (VaR) based diagnostics when applied to the post 2007 period that includes the recent financial crisis.
Sean Holly, M. Hashem Pesaran, and Takashi Yamagata. “A Spatio-temporal Model of House Prices in the US”, Journal of Econometrics, 158, 160-173, 2010.
Abstract: This paper provides an empirical analysis of changes in real house
prices in the USA using State level data. It examines the extent to
which real house prices at the State level are driven by fundamentals
such as real per capita disposable income, as well as by common shocks,
and determines the speed of adjustment of real house prices to
macroeconomic and local disturbances. We take explicit account of both
cross-sectional dependence and heterogeneity. This allows us to find a
cointegrating relationship between real house prices and real per capita
incomes with coefficients (1,−1),
as predicted by the theory. We are also able to identify a significant
negative effect for a net borrowing cost variable, and a significant
positive effect for the State level population growth on changes in real
house prices. Using this model we then examine the role of spatial
factors, in particular, the effect of contiguous states by use of a
weighting matrix. We are able to identify a significant spatial effect,
even after controlling for State specific real incomes, and allowing for
a number of unobserved common factors. We do, however, find evidence of
departures from long run equilibrium in the housing markets in a number
of States notably California, New York, Massachusetts, and to a lesser
extent Connecticut, Rhode Island, Oregon and Washington State.
Robert Dekle and Guillaume Vandenbroucke. " Whither Chinese Growth? A Sectoral Growth Accounting Approach ", Review of Development Economics, 14(3), 487–498, 2010.
Abstract: We perform a growth-accounting exercise for Chinese economic growth from 1978 to 2003, by decomposing Chinese growth in GDP per labor into the contributions arising from the agricultural, public, and private sectors; and the contribution arising from the reallocations of labor among these three sectors. The greatest contributor to overall labor productivity growth (contributing 30% of the overall) is the growth in total factor productivity in the private nonagricultural sector. The next largest contributor (26% of the overall) is the reallocation of labor from the agricultural sector to the nonagricultural sector.