We examine the causal relationship between energy efficiency and economic growth based on panel data for 56 high-and middle-income economies from 1978 to 2012. Using a panel vector autoregression approach, we find evidence of a long-run Granger causality from economic growth to lower energy intensity for all economies. We also find evidence of long-run bidirectional causality between lower energy intensity and higher economic growth for middle-income economies. This finding suggests that beyond climate benefits, middle-income economies may also earn an extra growth dividend from energy efficiency measures.Note: † denotes economies for which gaps in energy price observations are linearly interpolated using their consumer price index for multiple years.
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Empirical work in macroeconomics almost universally relies on the hypothesis of rational expectations. This paper departs from the literature by considering a variety of alternative expectations formation models. We study the econometric properties of a popular New Keynesian monetary DSGE model under different expectational assumptions: the benchmark case of rational expectations, rational expectations extended to allow for 'news' about future shocks, near-rational expectations and learning, and observed subjective expectations from surveys. The results show that the econometric evaluation of the model is extremely sensitive to how expectations are modeled. The posterior distributions for the structural parameters significantly shift when the assumption of rational expectations is modified. Estimates of the structural disturbances under different expectation processes are often dissimilar. The modeling of expectations has important effects on the ability of the model to fit macroeconomic time series. The model achieves its worse fit under rational expectations. The introduction of news improves fit. The best-fitting specifications, however, are those that assume learning. Expectations also have large effects on forecasting. Survey expectations, news, and learning all work to improve the model's one-step-ahead forecasting accuracy. Rational expectations, however, dominate over longer horizons, such as one-year ahead or beyond.
This paper exploits information from the term structure of survey expectations to identify news shocks in a a DSGE model with rational expectations. We estimate a structural business-cycle model with price and wage stickiness. We allow for both unanticipated and anticipated components ("news") in each structural disturbance: neutral and investment-specific technology shocks, government spending shocks, risk premium, price and wage markup shocks, and monetary policy shocks. We show that the estimation of a standard DSGE model with realized data obfuscates the identification of news shocks and yields weakly or non-identified parameters pertaining to such shocks. The identification of news shocks greatly improves when we re-estimate the model using data on observed expectations regarding future output, consumption, investment, government spending, inflation, and interest rates-at horizons ranging from one-period to five-periods ahead. The news series thus obtained largely differ from their counterparts that are estimated using only data on realized variables. Moreover, the results suggest that the identified news shocks explain a sizable portion of aggregate fluctuations. News about investment-specific technology and risk premium shocks play the largest role, followed by news about labor supply (wage markup) and monetary policy.
Receiver operating characteristic (ROC) curves can be misleading when they are constructed with selected samples. In this article, we describe heckroccurve, which implements a recently developed procedure for plotting ROC curves with selected samples. The command estimates the area under the ROC curve and a graphical display of the curve. A variety of plot options are available, including the ability to add confidence bands to the plot.
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