This paper looks at potential implications emerging from including shares as a control variable in fixed effect estimations. By shares I refer to the ratio of a sum of units over another, such as the share of immigrants in a city or school. As will be shown in this paper, a logarithmic...

In this tutorial we introduce recurrent neural networks (RNNs), and we describe the two most popular RNN architectures. These are the long short-term memory (LSTM) network and gated recurrent unit (GRU) network. Their common field of application is time series modeling, and we demonstrate their...

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...

This paper is motivated by our attempt to answer an empirical question: how is private health insurance take-up in Australia affected by the income threshold at which the Medicare Levy Surcharge (MLS) kicks in? We propose a new difference de-convolution kernel estimator for the location and size...

Due to the weak behavioral foundations of aggregate demand models, zonal travel cost models have been largely abandoned in favor of models based on individual observations. However, sample selection difficulties in individual-observation models often require the use of distribution-sensitive...

This paper shows through regression simulations that, when there are two highly collinear regressors, at least one of which has a simultaneous relationship with the dependent variable, t-ratios typically do not decline to non-significance as text book theory predicts. Coefficients and/or...

Textbook theory predicts that t-ratios decline towards zero in regressions when there is collinearity between two regressors. This paper shows that this often does not occur if the regression suffers from simultaneity or omitted variable bias. With more collinearity, t-ratios generally increase...