Why Are Teachers “Overpaid” in Developing Countries?

Labor and Human Capital,

Buyer Financing in Pull Supply Chains: Zero-Interest Early Payment or In-House Factoring?

This study investigates the efficacy of zero-interest early payment financing (alternatively referred to as early payment) and positive-interest in-house factoring financing in a pull supply chain with a capital-constrained manufacturer selling a product through a capital-abundant retailer. Early payment is the prepayment of a wholesale cost to the manufacturer, whereas in-house factoring is a loan service provided to the manufacturer by a branch financing firm of the same retailer. We find that the retailer prefers early payment financing to bank financing when the manufacturer’s production cost is low. If the retailer instead offers positive-interest in-house factoring financing to the manufacturer, then the financing equilibrium domain enlarges as compared to bank financing. Interestingly, early payment financing can outplay positive-interest in-house factoring financing if the production cost is considerably low; otherwise, vice versa. When the production cost is big enough, the retailer will not provide either early payment or in-house factoring. Furthermore, our main qualitative result sustains with an identical wholesale price across all three financing schemes and the financing equilibrium domain of early payment shrinks as demand variability grows

Cooperative Spectrum Sensing

Non

Testing Homogeneity in Panel Data Models with Interactive Fixed Effects

This paper proposes a residual-based Lagrange Multiplier (LM) test for slope homogeneity in large-dimensional panel data models with interactive fixed effects. We first run the panel regression under the null to obtain the restricted residuals and then use them to construct our LM test statistic. We show that after being appropriately centered and scaled, our test statistic is asymptotically normally distributed under the null and a sequence of Pitman local alternatives. The asymptotic distributional theories are established under fairly general conditions that allow for both lagged dependent variables and conditional heteroskedasticity of unknown form by relying on the concept of conditional strong mixing. To improve the finite-sample performance of the test, we also propose a bootstrap procedure to obtain the bootstrap p-values and justify its validity. Monte Carlo simulations suggest that the test has correct size and satisfactory power. We apply our test to study the Organization for Economic Cooperation and Development economic growth model.</jats:p

Improvement in Finite-Sample Properties of GMM-Based Wald Tests

  GMM-based Wald tests tend to overreject when used for small samples, mainly due to inaccurate estimation of the weighting matrix. This article proposes applying the shrinkage method to address this problem. Using a possibly-misspecied factor model, the shrinkage method can provide a good estimator for the weighting matrix, and hence improve the nite-sample performance of the GMM-based Wald tests.  This paper is accepted by Computational Statistics