Nonparametric correlation models for portfolio allocation

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural breaks in correlations. Only when correlations are constant does the parametric DCC model deliver the best outcome. The methodologies are illustrated by evaluating two interesting portfolios. The first portfolio consists of the equity sector SPDRs and the S&P 500, while the second one contains major currencies. Results show the nonparametric model generally dominates the others when evaluating in-sample. However, the semiparametric model is best for out-of-sample analysis.     

Anatomy of Russia’s market segmentation1

Based on a relationship between price difference and demand difference among locations, the role of various market frictions in causing segmentation of the Russian goods market is analysed. The spatial sample covers most of Russian regions (70 of the 89); the data are annual, spanning 1992 to 2000. Spatial disconnectedness of regions is found to be responsible for about 70 percent of the average price differential, while the rest is caused by ‘artificial’ impediments to market integration such as regional protectionism, organized crime and intra‐region shipping conditions.     

External Financing,Growth and Stock Returns

In this paper we investigate the relation of the value/growth anomaly with the anomaly on corporate financing activities. We confirm and expand earlier results that value/growth and external financing indicators are, to some degree, related predictors of stock returns in the cross section. We show that external financing indicators are incrementally informative since they pick up stock returns associated with earnings quality. Portfolios that combine information from both these indicators generate significantly higher returns than portfolios containing each individual indicator. More importantly, our analysis strongly suggests that the external financing anomaly is, to some extent, distinct from the value/growth anomaly, in that it may also reflect investors’ misunderstanding of the effects of opportunistic earnings management.     

Habit Formation in an Overlapping Generations Model with Borrowing Constraints

We introduce habit‐formation in the three‐period OLG borrowing‐constrained framework of Constantinides et al. (2002) by allowing the utility of the middle‐aged (old) to depend on consumption when young (middle‐aged). This specification enables us to separate the effect of the two habit parameters (middle‐aged and old) since each representative age‐group can face different levels of habit persistence. The two‐habit setup underlines some important issues with regards to savings and security returns which do not always conform to the standard findings in the literature. In addition, the model produces equity premium consistent with US data for relatively small levels of risk aversion.     

Modelling Electricity Prices: International Evidence*

This article analyses the evolution of electricity prices in deregulated markets. We present a general class of models that simultaneously takes into account several factors: seasonality, mean reversion, GARCH behaviour and time‐dependent jumps. The models are applied to daily equilibrium spot prices of eight electricity markets. Eight different nested models were estimated to compare the relative importance of each factor in each of the eight markets. We find strong evidence that electricity equilibrium prices are mean‐reverting, with volatility clustering (GARCH) and with jumps of time‐dependent intensity, even after adjusting for seasonality.     

Industry Structure and Corporate Debt Maturity

We examine how industry competition affects firms’ choice of short‐term debt. We find that the percentage of short‐term debt is positively related to industry concentration at low levels of concentration, and inversely related to industry concentration at higher levels of concentration. This nonlinear relation is stronger in industries where firms are either more homogeneous or compete more aggressively. Moreover, we find that firms with shorter‐maturity debt are less aggressive than their rivals in the product market. The overall evidence suggests that although financial contracts alleviate agency problems, they exacerbate the risk of predation.     

Large-scale mortality shocks and the Great Irish Famine 1845–1852

This paper considers the consequences of a large scale mortality shock arising from a famine or epidemic for long run economic and demographic development. The Great Irish Famine of 1845–1852 is taken as a case-study and is incorporated as an exogenous mortality shock into the type of long-run unified growth theory pioneered by Galor and Weil (1999, 2000), and modelled by Lagerlöf (2003a,b) among others. Through calibration, the impact of such a mortality shock occurring on the cusp of a country's transition from a Malthusian to a Modern Growth regime is then depicted.     

Economic importance and statistical significance: Guidelines for communicating empirical research

Abstract

A critical objective for many empirical studies is a thorough evaluation of both substantive importance and statistical significance. Feminist economists have critiqued neoclassical economics studies for an excessive focus on statistical machinery at the expense of substantive issues. Drawing from the ongoing debate about the rhetoric of economic inquiry and significance tests, this paper examines approaches for presenting empirical results effectively to ensure that the analysis is accurate, meaningful, and relevant for the conceptual and empirical context. To that end, it demonstrates several measurement issues that affect the interpretation of economic significance and are commonly overlooked in empirical studies. This paper provides guidelines for clearly communicating two distinct aspects of “significance” in empirical research, using prose, tables, and charts based on OLS, logit, and probit regression results. These guidelines are illustrated with samples of ineffective writing annotated to show weaknesses, followed by concrete examples and explanations of improved presentation.     

Trading frequency and volatility clustering

Volatility clustering, with autocorrelations of the hyperbolic decay rate, is unquestionably one of the most important stylized facts of financial time series. This paper presents a market microstructure model that is able to generate volatility clustering with hyperbolically decaying autocorrelations via traders with multiple trading frequencies, using Bayesian information updates in an incomplete market. The model illustrates that signal extraction, which is induced by multiple trading frequencies, can increase the persistence of the volatility of returns. Furthermore, we show that the volatility of the underlying time series of returns varies greatly with the number of traders in the market.     

A Comparison of EPI Sampling, Probability Sampling, and Compact Segment Sampling Methods for Micro and Small Enterprises

Finding an efficient method for sampling micro- and small-enterprises (MSEs) for research and statistical reporting purposes is a challenge in developing countries, where registries of MSEs are often nonexistent or outdated. This lack of a sampling frame creates an obstacle in finding a representative sample of MSEs. This study uses computer simulations to draw samples from a census of businesses and non-businesses in the Tshwane Municipality of South Africa, using three different sampling methods: the traditional probability sampling method, the compact segment sampling method, and the World Health Organization's Expanded Programme on Immunization (EPI) sampling method. Three mechanisms by which the methods could differ are tested, the proximity selection of respondents, the at-home selection of respondents, and the use of inaccurate probability weights. The results highlight the importance of revisits and accurate probability weights, but the lesser effect of proximity selection on the samples' statistical properties.