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| Bonfiglio, Andrea. |
| The objective of this article is to assess labour income and employment effects in Romania coming from rural development and structural policies defined in the proposed 2007-09 EU accession financial package. The methodology used is based on a multiregional I-O model derived by a three-stage estimation procedure. Main results show that EU accession will lead to large positive effects in Romania, which vary according to the region considered. In this connection, the South and the North- East regions are those on which benefits tend to concentrate. Finally, policy would seem to reduce regional and sectoral income disparities, leading to more balanced development. On the contrary, in terms of employment, policy would increase divergences, albeit, from an... |
| Tipo: Conference Paper or Presentation |
Palavras-chave: EU accession; Rural development; Structural actions; Policy impact; Multiregional I-O model; International Relations/Trade; C82; R15; R58. |
| Ano: 2005 |
URL: http://purl.umn.edu/24492 |
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| Wolff, Hendrik; Chong, Howard; Auffhammer, Maximilian. |
| This paper examines the consequences of data error in data series used to construct aggregate indicators. Using the most popular indicator of country level economic development, the Human Development Index (HDI), we identify three separate sources of data error. We propose a simple statistical framework to investigate how data error may bias rank assignments and identify two striking consequences for the HDI. First, using the cutoff values used by the United Nations to assign a country as 'low', 'medium', or 'high' developed, we find that currently up to 45% of developing countries are misclassified. Moreover, by replicating prior development/macroeconomic studies, we find that key estimated parameters such as Gini coefficients and speed of convergence... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Measurement Error; International Comparative Statistics; Research Methods/ Statistical Methods; O10; C82. |
| Ano: 2008 |
URL: http://purl.umn.edu/6502 |
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| Wolff, Hendrik; Chong, Howard; Auffhammer, Maximilian. |
| This paper examines the consequences of data error in data series used to construct aggregate indicators. Using the most popular indicator of country level economic development, the Human Development Index (HDI), we identify three separate sources of data error. We propose a simple statistical framework to investigate how data error may bias rank assignments and identify two striking consequences for the HDI. First, using the cutoff values used by the United Nations to assign a country as ‘low’, ‘medium’, or ‘high’ developed, we find that currently up to 45% of developing countries are misclassified. Moreover, by replicating prior development/macroeconomic studies, we find that key estimated parameters such as Gini coefficients and speed of convergence... |
| Tipo: Working or Discussion Paper |
Palavras-chave: Measurement Error; International Comparative Statistics; International Development; O10; C82. |
| Ano: 2009 |
URL: http://purl.umn.edu/49763 |
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| Egelkraut, Thorsten M.; Garcia, Philip; Irwin, Scott H.; Good, Darrel L.. |
| Using 1971-2000 data, we examine the accuracy of corn and soybean production forecasts provided by the USDA and two private agencies. All agencies improved their forecasts as the harvest progressed, and forecast errors were highly correlated and unbiased. The relative forecast accuracy of the agencies varied by crop and month. For corn, USDA’s forecasts ranked as most accurate of the three agencies in all periods except for august during the recent period and improved most markedly as harvest progressed. For soybeans, forecast errors were very similar, with the private agencies ranking as most accurate for August and September and making largest relative improvements for August during the recent period. The USDA forecasts were dominant for October and... |
| Tipo: Journal Article |
Palavras-chave: Corn; Private agencies; Production forecasts; Soybeans; USDA; Q11; Q13; C82; Q18. |
| Ano: 2003 |
URL: http://purl.umn.edu/37835 |
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