The econometrics literature proposed several new causal machine learning methods (CML) in the past few years. These methods harness the strength of machine learning methods to flexibly model the relationship between the treatment, outcome and confounders, while providing valid inferential...

As part of the Kyoto Protocol, many countries have committed themselves tosubstantially reduce the emission of greenhouse gases within a politically imposed timeconstraint. Investment subsidies can be an important instrument to stimulate the adoption ofenergy-saving technologies to achieve...

The recent dramatic change in energy supply in Japan has prompted a search for a new energy-environment-economic efficiency policy, in which a compromise has to be found between a sufficient supply of energy resources, the development of low carbon emission technology, and a continuation of...

This paper analyses the adoption of energy-efficiency enhancing technologies by heterogeneous firms. The fact that energy use does not only cause external environmental costs through pollution, but also directly affects the profitability of the firm and hence its behaviour on input and output...

In this paper, we present a directed search model of the housing market. The pricing mechanism we analyze reflects the way houses are bought and sold in the United States. Our model is consistent with the observation that houses are sometimes sold above, sometimes below and sometimes at the...

This paper proposes a score-driven model for filtering time-varying causal parameters through the use of instrumental variables. In the presence of suitable instruments, we show that we can uncover dynamic causal relations between variables, even in the presence of regressor endogeneity which...