The rapid growth of ASEAN economies, the People's Republic of China and India (called ACI henceforth) - major drivers of Asia and the world economy - during the last five decades has caused significant strains on their scarce resources, particularly energy and contributed to serious problems of...

In a model where firms face a continuous choice of how much to invest in environmental innovation, we show that an ever stricter environmental policy does not always lead to ever cleaner production methods and ever lower production of polluting goods. It does so when the abatement technology is...

This paper analyzes socially optimal forest taxation when the government has a binding tax revenue requirement. In the Faustmann model the optimal design of forest taxation consists of non-distortionary taxes, such as site productivity tax, site value tax or profit tax. A combination of...

Papers on optimal harvesting regimes for maximizing land expectation value (LEV) that compare different logging practices often ignore differences in variable costs and in damages on the residual stand between logging practices. We use data on a multi-age, multi-species forest in East-Kalimantan...

We study the evolution of EC merger decisions over the first 25 years of common European merger policy. Using a novel dataset at the level of the relevant antitrust markets and containing all merger cases scrutinized by the Commission over the 1990-2014 period, we evaluate how consistently...

With the rapid expansion of private forest plantations worldwide, their impacts on local development are under scrutiny by NGOs and researchers alike. This study investigates the impacts of private forest plantations on local infrastructure and social services in rural Tanzania. We take a...

Quantifying factors giving rise to temporal variation in forest fires is important for advancing scientific understanding and improving fire prevention. We demonstrate that eighty percent of the large year-to-year variation in forest area burned in California can be accounted for by variation in...

This paper develops a machine-learning method that allows researchers to estimate heterogeneous treatment effects with panel data in a setting with many covariates. Our method, which we name the dynamic causal forest (DCF) method, extends the causal-forest method of Wager and Athey (2018) by...