Consider a bipartite network where <i>N</i> consumers choose to buy or not to buy <i>M</i> different products. This paper considers the properties of the logistic regression of the <i>N</i> × <i>M</i> array of "i-buys-j" purchase decisions, <i>[Y_ij]_{1≤i≤N,≤j≤M}</i>, onto known functions of consumer and product attributes...

Three potential sources of bias present complications for estimating the half-life of purchasing power parity deviations from panel data. They are the bias associated with inapproiate aggregation across heterogeneous coefficients, time aggregation of commodity prices, and downward bias in...

We study the panel DOLS estimator of a homogeneous cointegration vector for a balanced panel of N individuals observed over T time periods. Allowable heterogeneity across individuals include individual-specific time trends, individual-specific fixed effects and time-specific effects. The...

We propose a generalization of the linear quantile regression model to accommodate possibilities afforded by panel data. Specifically, we extend the correlated random coefficients representation of linear quantile regression (e.g., Koenker, 2005; Section 2.6). We show that panel data allows the...

We study identification in a binary choice panel data model with a single predetermined binary covariate (i.e., a covariate sequentially exogenous conditional on lagged outcomes and covariates). The choice model is indexed by a scalar parameter θ, whereas the distribution of unit-specific...