Panel data in many econometric applications exhibit a nested (hierarchical) structure. For example, data on "rms may be grouped by industry, or data on air pollution may be grouped by observation station within a city, city within a country, and by country. In these cases, one can control for unobserved group and sub-group e!ects using a nested-error component model. A double-nested unbalanced ...

Econometric models wishing to estimate relevant parameters for agricultural policy analysis are increasingly relying on unbalanced panels of farm-level data. Since in the agricultural economics literature such models have often been estimated through simplified approaches, in this paper we try to verify whether the adoption of more sophisticated panel data techniques may impact the estimation r...

We perform specification tests of unbalanced panel data models for stock return prediction using an estimate of the coefficient covariance matrix robust to spatial heteroskedasticity. We apply estimators of individual effects and time effects in unbalanced panel models. For a panel of 1243 US firms for the period 1985–2002 we find that industry effects are significant and interact with firm cha...

Introduction Different types of data are generally available for empirical analysis, namely, time series, cross section, and panel. A data set containing observations on a single phenomenon observed over multiple time periods is called time series (e.g., GDP for several quarters or years). In time series data, both the values and the ordering of the data points have meaning. In cross-section da...

Analysing a large sample of 1980–2004 unbalanced panel data, the current study presents comparative global evidence on the role of (income) inequality in poverty reduction. The evidence involves both an indirect channel via the tendency of high inequality to decrease the rate at which income is transformed to poverty reduction and the tendency of rising inequality to increase poverty. Based on ...

Extending the work by Hausman and Wise (1979), Ridder (1992), Wooldridge (1995) and Ryu (2001), this paper proposes a new and simpler way of accounting for attrition in unbalanced panel data. Cross-sectional units are dissipated over time, possibly in a nonrandom fashion, thus negating the initial randomization. The key element of the current approach is to model the attrition process jointly w...

Modeling pavement performance by combining field and experimental data The accurate prediction of pavement performance is important for efficient management of the surface transportation infrastructure. By reducing the error of the pavement deterioration prediction, agencies can obtain significant budget savings through timely intervention and accurate planning. The goal of this research was to...