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This paper provides comparisons of a variety of time series methods for short run forecasts of the main greenhouse gas, carbon dioxide, for the United States, using a recently released state level data set from 1960-2001. We test the out-of-sample performance of univariate and multivariate forecasting models by aggregating state level forecasts versus forecasting the aggregate directly. We find evidence that forecasting the disaggregate series and accounting for spatial effects drastically improves forecasting performance under Root Mean Squared Forecast Error Loss. Based on the in-sample observations we attempt to explain the emergence of voluntary efforts by states to reduce greenhouse gas emissions. We find evidence that states with decreasing per capita emissions and a "greener" median voter are more likely to push towards voluntary cutbacks in emissions.

This paper tests the out of sample predictive ability of reduced form models found in the literature on forecasting CO2 emissions. We show that for a newly available panel data set covering the fifty U.S. States and Washington D.C. during the years 1960 - 2000, the benchmark models found in the literature are outperformed by over 3000 of the considered models. A search over a large universe of models selects a ”best” performing model using the mean square forecast error from a simulated out of sample forecast experiment. Forecasts of aggregate CO2 emissions for the United States are provided.

Privatization generally enhances firm-level efficiency. The impact of privatization on fiscal efficiency has, however, been overlooked. Using the 'tax-smoothing' ideas articulated by R. Barro (1979) [On the determination of the public debt. Journal of Political Economy, 87, 940-971] and by H. Bohn (1990) [Tax smoothing with financial instruments. American Economic Review, 80, 1217-1230], we argue that privatization may have an important impact on the welfare losses associated with tax collection. This impact can either enhance or erode the efficiency of taxation. We hypothesize that countries that benefit in terms of fiscal efficiency will privatize aggressively while countries that enjoy fiscal benefits as a result of state ownership will show little interest in privatization. Statistical tests are conducted that provide considerable support for the hypothesis. Key words--privatization, tax smoothing, fiscal policy doi:10.1016/j.worlddev.2005.07.016

We compare the most common reduced-form models used for emissions forecasting, point out shortcomings, and suggest improvements. Using a U.S. state-level panel data set of CO2 emissions, we test the performance of existing models against a large universe of potential reduced-form models. We find that leading models in the literature, as well as models selected based on an emissions per capita loss measure or different in-sample selection criteria, perform significantly worse compared to the best model chosen based directly on the out-of-sample loss measure defined over aggregate emissions. [ABSTRACT FROM AUTHOR]

This paper provides comparisons of a variety of time-series methods for short-run forecasts of the main greenhouse gas, carbon dioxide, for the United States, using a recently released state-level data set from 1960–2001. We test the out-of-sample performance of univariate and multivariate forecasting models by aggregating state-level forecasts versus forecasting the aggregate directly. We find evidence that forecasting the disaggregate series and accounting for spatial effects drastically improves forecasting performance under root mean squared forecast error loss. Based on the in-sample observations we attempt to explain the emergence of voluntary efforts by states to reduce greenhouse gas emissions. We find evidence that states with decreasing per capita emissions and a “greener” median voter are more likely to push toward voluntary cutbacks in emissions. [ABSTRACT FROM AUTHOR]