Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra
Опубликовано на портале: 26-11-2007
Anke Reichhuber, Till Requate
Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra.
2007.
No. 2007-07.
This paper presents a cost-benefit analysis of three different use systems for the
remaining cloud forests in Ethiopia which at present are being depleted at a rate
of 8% per year. These use systems are traditional conversion to crop land, sustainable
management of the forest (e.g. by growing high-quality semi-forest coffee), and strict
protection. We find that conversion to cropland yields the highest net present income
value for the local population, and at discount rates of 10% is even in the best
interests of the country. For discount rates of at 5% or lower, sustainable forest
use is in the best interests of the country. Taking into account the global benefits
of biodiversity conservation and carbon storage, sustainable forest management yields
the highest total economic value.


An Efficient Filtering Approach to Likelihood Approximation for State-Space Representations [статья]
Опубликовано на портале: 26-11-2007
David N. DeJong, Hariharan Dharmarajan, Roman Liesenfeld, Jean-Francois Richard
Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra.
2007.
No. 2007-25.
We develop a numerical filtering procedure that facilitates efficient likelihood
evaluation in applications involving non-linear and non-gaussian state-space models.
The procedure approximates necessary integrals using continuous or piecewise-continuous
approximations of target densities. Construction is achieved via efficient importance
sampling, and approximating densities are adapted to fully incorporate current information.


Опубликовано на портале: 26-11-2007
Helmut Herwartz
Economics Working Papers of Department of Economics and Business, Universitat Pompeu Fabra.
2007.
No. 2007-09.
The paper provides Monte Carlo evidence on the performance of general-to-specific
and specific-to-general selection of explanatory variables in linear (auto)regressions.
In small samples the former is markedly inefficient in terms of ex-ante forecasting
performance.

