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...

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...

This paper looks at potential implications emerging from including “shares” as a control variable in fixed effect estimations. By shares we 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...

Despite similar levels of per capita income, education, and technology the development of labour shares in OECD countries has displayed different patterns since 1960. The paper examines the role of demography in this regard. Employing an overlapping generations model we first examine the...

Despite similar levels of per capita income, education, and technology the development of labour shares in OECD countries has displayed different patterns since 1960. The paper examines the role of demography in this regard. Employing an overlapping generations model we first examine the...

Despite similar levels of per capita income, education, and technology the development of labour shares in OECD countries has displayed different patterns since 1960. The paper examines the role of demography in this regard. Employing an overlapping generations model we first examine the...

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...