A Rise by Any Other Name? Sensitivity of Growth Regressions to Data Source

Measured rates of growth in real per capita income differ drastically depending on the data source. This phenomenon occurs largely because data sets differ in whether and how they adjust for changes in relative prices across countries. Replication of several recent studies of growth determinants shows that results are sensitive in important ways to the choice of data. Previous warnings against using data adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.growth, measurement

The Other Side of the Moon: The Data Problem in Analyzing Growth Determinants

Replication of two recent studies of growth determinants shows that results are sensitive to the choice of data from which growth rates are calculated, especially with respect to whether economic convergence has occurred. Previous warnings against using data that has been adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.http://deepblue.lib.umich.edu/bitstream/2027.42/40068/3/wp682.pd

A Rise By Any Other Name? Sensitivity of Growth Regressions to Data Source

Measured rates of growth in real per capita income differ drastically depending on the data source. This phenomenon occurs largely because data sets differ in whether and how they adjust for changes in relative prices across countries. Replication of several recent studies of growth determinants shows that results are sensitive in important ways to the choice of data. Previous warnings against using data adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.http://deepblue.lib.umich.edu/bitstream/2027.42/64394/1/wp889.pd

A Rise By Any Other Name? Sensitivity of Growth Regressions to Data Source

Measured rates of growth in real per capita income differ drastically depending on the data source. This phenomenon occurs largely because data sets differ in whether and how they adjust for changes in relative prices across countries. Replication of several recent studies of growth determinants shows that results are sensitive in important ways to the choice of data. Previous warnings against using data adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.Growth, Measurement

The Other Side of the Moon: The Data Problem in Analyzing Growth Determinants

Replication of two recent studies of growth determinants shows that results are sensitive to the choice of data from which growth rates are calculated, especially with respect to whether economic convergence has occurred. Previous warnings against using data that has been adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.Growth; Measurement; Developing Economies

Supply-Side Performance and Structure in the Czech Republic (1995-2005)

In this paper, we apply the aggregate production function to approximate the path of potential output. We use a time-varying NAIRU to derive the amount of potential labour and a newly developed measure of capital services to account for the productive impact of capital. In addition, trend total factor productivity is estimated. Production functions for the key sectors (Agriculture, Industry, etc.) are also calculated, exploring the growth accounting approach and decomposition of total factor productivity growth. During 1995--2005, the growth in potential output was constrained by a gradual increase in the NAIRU, a temporary drop in investment activity and, most importantly, by only a modest rise in total factor productivity. In this period, the Czech economy also suffered from a structural burden, i.e. all growth in total factor productivity was exclusively due to better utilisation of resources, given their initial allocation, with an even negative contribution of resource reallocation. Just from 2001 onwards, we observe substantial improvements in supply-side performance, except for the functioning of the labour market.. Capital services, factor allocation and utilisation, growth accounting, NAIRU, potential output, production function, structural changes, total factor productivity.

Measuring Multifactor Productivity Growth

This paper quantifies and examines the contribution of capital, labour and multifactor productivity (MFP) to GDP growth and analyses the role of measurement of capital and labour inputs for the MFP estimate, using a comprehensive growth accounting exercise for 14 OECD countries. For most OECD countries, the strongest contributions to GDP growth over the past decade have come from growth in total capital input and MFP. This is to some extent related to an increasing role of information and telecommunication technologies in economic growth, particularly over the 1995-2003 period. The importance of measurement issues varies substantially with the type of measurement issue being considered. Substantial differences are observed between employment and hours worked based MFP growth rates. Also, the respective weights with which capital and labour enter the growth accounting equation, and thus, the assumptions concerning the efficiency of production and competition in product markets, significantly influence the resulting MFP estimate. Finally, the results suggest that policy conclusions on the basis of different empirical studies should be made very carefully, in particular as regards the time period for which the respective studies have been undertaken, as well as whether actual or trended time series are being considered. Ce document évalue et examine la contribution du capital, de la main-d'oeuvre et de la productivité globale des facteurs (PGF) à la croissance du PIB, et analyse le rôle de la mesure des apports de capital et de travail dans l'estimation de la PGF, par un travail complet de quantification comptable de la croissance portant sur 14 pays de l'OCDE. Dans la plupart des cas, c'est la croissance des apports totaux de capital et celle de la PGF qui ont contribué le plus fortement à la croissance du PIB ces dix dernières années. Cette évolution est liée dans une certaine mesure au rôle de plus en plus grand des technologies de l'information et de la communication dans la croissance économique, en particulier pendant la période 1995-2003. L'importance des questions de mesure varie beaucoup en fonction de leur type. On observe des différences considérables entre les taux de croissance de la PGF fondés sur l'emploi et sur les heures travaillées. En outre, la part relative du capital et du travail dans l'équation comptable de la croissance et, par conséquent, les hypothèses concernant l'efficacité de la production et la concurrence sur les marchés de produits, influent sensiblement sur l'estimation de la PGF obtenue. Enfin, il semble qu'on ne puisse tirer de conclusions des différentes études empiriques qu'en exerçant la plus grande prudence, en particulier en vérifiant la période à laquelle ces études ont été effectuées, et en déterminant si les séries chronologiques considérées sont des séries réelles ou des séries de tendances.

A rise by any other name? Sensitivity of growth regressions to data source

Measured rates of growth in real per capita income differ drastically depending on the data source. This phenomenon occurs largely because data sets differ in whether and how they adjust for changes in relative prices across countries. Replication of several recent studies of growth determinants shows that results are sensitive in important ways to the choice of data. Previous warnings against using data adjusted to increase cross-country comparability to study within-country patterns over time (growth rates) have been largely ignored at the cost of possibly contaminating the conclusions.

The Mirage of Convergence: Why Poor Countries May Only Seem to Be Closing the Income Gap

Results of numerous cross-country growth regressions have been found to be sensitive to specification, time period or sample coverage. Several authors have observed that results may depend on the source and data collection methods for right-hand side variables. In this paper we suggest that a more fundamental problem may exist with respect to the growth rates used in the majority of studies. Differences in measured growth rates are severe across widely-used sources. More critically, these differences are correlated with countries’ level of development. As an illustration, we show that the results of two recent studies depend critically on which data set is used to derive the growth measure.Growth; Measurement; Developing Economies.