Sectoral Energy- and Labour-Productivity Convergence



coefficient β, for each sector. A negative estimated coefficient β indicates the existence of so-
called
β-convergence. We start in section 5.1 by testing for unconditional convergence,
assuming that energy- and labour productivity converge towards a unique steady state for all
countries included in the data set. In section 5.2 we relax this assumption and test for
conditional convergence, assuming productivity levels to converge towards multiple steady
states that are conditional on country-specific characteristics. Finally, as part of this analysis
we try to identify the country-specific characteristics that determine (differences in) energy-
and labour-productivity growth across countries.

5.1 Unconditional β-convergence

We test for unconditional β-convergence by regressing for each sector the growth rate (g) of,
respectively, energy- and labour productivity
(y), on its initial level (and a constant a),
generating an estimate of
β, according to:

git = log(y)i,t - log(y)i,t-1 = a + β ln(y)i,t-1 + eu                                            (1)

with i and t denoting, respectively, the cross-country and the time-series dimension,
while
εit is the standard error. Following Islam (1995) we use five-year time intervals in order
to reduce the influence of business-cycle fluctuations and serial correlation of the error term.
Hence, the growth rate (
g) in equation (1) is an average over a five-year period (if t = 1975,
for example,
t-1 = 1970). The results are presented in Table 2.

(Table 2, Page 28)

From the table it can be seen that we obtain a statistically significant negative estimate of β
for energy-productivity growth in most sectors, except for Total (i.e., the macroeconomic
level), Chemicals, Iron and Steel, Non-Ferrous Metals, Paper and Wood. In terms of labour-
productivity growth we found
β to be statistically significant in all sectors, except for
aggregate Manufacturing and Non-Ferrous Metals.14

14 We also estimated equation (1) including a period-specific fixed effect η t according to git = α + β ln(y ) i,t-1 + η t
+ εit . The regression results with these period dummies included do not substantially improve the estimates in
most sectors, except for Non-Ferrous Metals and in terms of labour productivity also for Chemicals, Iron and
Steel and Machinery. These findings suggest, that in spite of a few exceptions, in general there is not much
evidence for substantial differences in growth rates between the time periods included. Details are available
upon request.

11



More intriguing information

1. Labour Market Flexibility and Regional Unemployment Rate Dynamics: Spain (1980-1995)
2. The Impact of Minimum Wages on Wage Inequality and Employment in the Formal and Informal Sector in Costa Rica
3. The name is absent
4. Detecting Multiple Breaks in Financial Market Volatility Dynamics
5. The name is absent
6. Perceived Market Risks and Strategic Risk Management of Food Manufactures: Empirical Results from the German Brewing Industry
7. Strategic Effects and Incentives in Multi-issue Bargaining Games
8. The name is absent
9. The name is absent
10. Regulation of the Electricity Industry in Bolivia: Its Impact on Access to the Poor, Prices and Quality
11. Nonparametric cointegration analysis
12. Putting Globalization and Concentration in the Agri-food Sector into Context
13. EXPANDING HIGHER EDUCATION IN THE U.K: FROM ‘SYSTEM SLOWDOWN’ TO ‘SYSTEM ACCELERATION’
14. EFFICIENCY LOSS AND TRADABLE PERMITS
15. The name is absent
16. Public-private sector pay differentials in a devolved Scotland
17. Partner Selection Criteria in Strategic Alliances When to Ally with Weak Partners
18. Ultrametric Distance in Syntax
19. Apprenticeships in the UK: from the industrial-relation via market-led and social inclusion models
20. Firm Creation, Firm Evolution and Clusters in Chile’s Dynamic Wine Sector: Evidence from the Colchagua and Casablanca Regions