Convergence of labor productivity across the US states

Most studies of labor productivity convergence among US states base their analyses on state-level GDP per worker. Such aggregated analysis may hide important information about the role of sectors, and changes in the sectoral composition of these economies, in explaining economy-wide convergence results. Using highly disaggregated data for the period 1987–2015 from the US Bureau of Economic Analysis, we examine sectoral unconditional convergence in labor productivity in the US states. Our results demonstrate a general slowing down in the rate of convergence of labor productivity in the latter years of this period. The sectoral analysis also indicates that manufacturing was the primary driver of convergence during the 1987–1997 period, which had the highest rate of convergence; the role of this sector, however, has diminished in recent years. Several factors—such as the decline in interstate migration, rising housing costs in major cities, agglomeration, and structural changes in the US economy that have reduced the role of manufacturing—may have contributed to the rise in the labor productivity differential among US states.     

Labor productivity growth: disentangling technology and capital accumulation

How much of the convergence in labor productivity that we observe in manufacturing is due to convergence in technology versus convergence in capital-labor ratios? To shed light on this question, we introduce a nonparametric counterfactual decomposition of labor productivity growth into growth of the capital-labor ratio (K/L), technological productivity (TEP) and total factor productivity (TFP). Our nonparametric specification enables us to model technology allowing for heterogeneity across all relevant dimensions (i.e. countries, sectors and time). Using data spanning from the 1960s to the 2000s, covering 42 OECD and non OECD countries across 11 manufacturing sectors, we find TEP and TFP to account for roughly 46 and ?6% of labor productivity growth respectively, on average. While technological growth at the world level is driven primarily by the US and a handful of other OECD countries, we find strong evidence of convergence in both technology and capital-labor ratios. Interestingly, very few of the usual growth determinants are found to enhance the process of technological catching-up.     

Labor shares in the old and new EU member states - Sectoral effects and the role of relative prices

The paper studies the labor share among countries of the European Union, with a particular attention to the newer member states of Central and Eastern Europe (CEEU). We find that CEEU countries typically have lower labor shares than older EU member states, both in the aggregate and at the sectoral level. Structural change, while quite pronounced among the CEEU economies, plays only a minor role in the evolution of the labor share. The exception is agriculture, which for some countries has a sizable impact on the level and dynamics of the labor share - partly because of important measurement problems. We also find that a significant part of the difference in conventionally measured labor shares between the more developed EU countries and less developed CEEU countries can be attributed to differences in relative prices. This is consistent with a productivity-based explanation: we show that a simple, calibrated two-sector model with sectoral productivity differentials can explain 36–71% of cross-country variations in the non-agricultural labor share.     

Regional divergence and club convergence in India

This paper examines regional divergence in income across different states in India, and estimates convergence clubs endogenously. The paper makes two useful contributions. First, the data is analyzed using a novel method due to Phillips and Sul (2007) leading to different conclusions in comparison to past studies, and secondly sectoral level data is employed which to our knowledge has not been employed in the literature before. Applying the novel approach to panel data relating to fifteen major states of India for the period 1968/69–2008/09, the results display significant divergence in per capita income across states at the aggregate and sectoral levels. There is also evidence of convergence clubs and variations in the number and composition of clubs across sectors. While three clubs are identified at the aggregate level, at the sectoral level we find three clubs in the industrial sector, two clubs are identified in both the agriculture and services sectors. The final part of the paper deals with the policy implications.     

Finance and sources of growth: evidence from the U.S. states

How does financial development affect economic growth: through its impact on accumulation of physical and human capital or by boosting total factor productivity (TFP) growth? We use a new data set on output, inputs, and total factor productivity for the US states to study this question. Unlike previous cross-country research that tries to disentangle the channels through which financial development impacts growth, we use a plausibly exogenous measure of financial development: the timing of banking deregulation across states during the period 1970–2000. At the same time our new data set allows us to go beyond what was previously done in the state banking deregulation literature and identify whether finance impacts states’ input accumulation or TFP growth. We find, in line with existing cross-country studies, that deregulation boosts growth by accelerating both TFP growth and the accumulation of physical capital without having any impact on human capital. In contrast to the cross-country studies, we also find that the effects of deregulation are largely independent of states’ initial level of development; both rich and poor states grow faster after deregulation. Additionally, since our data set breaks down aggregate output into three sectors: agriculture, manufacturing, and the remaining industries, we are able to show that deregulation accelerates the growth of productivity in manufacturing. This last finding answers an important critique of the banking deregulation studies which asserts that observed growth effects may be coming from the growth of financial industry itself and not from the beneficial effect of finance on other industries, such as manufacturing.     

A two-sector Kaleckian model of growth and distribution with endogenous productivity dynamics

This study extends a two-sector Kaleckian model of output growth and income distribution by incorporating endogenous labour productivity growth. The model is composed of investment goods and consumption goods production sectors. The impact of a change in wage and profit shares on capacity utilisation and output growth rates at the sectoral and aggregate levels are identified. The study reveals short-run cyclical capacity utilisation rates and productivity growth dynamics. Even if the short-run steady state is stable, the capital accumulation rate in the consumption goods sector must decrease more than that in the investment sector for long-run stability. When simultaneous rises in profit shares in both the sectors affect long-run aggregate economic growth differently at a steady state, the distributional interests between the same class in different sectors may hamper the long-run economic growth. A policy message is that the effect of income distribution on industrial output growth is not always beneficial. These phenomena are specific to two-sector models and cannot be observed when using conventional aggregate growth models.     

Dynamics of sectoral business cycle comovement

Sectoral comovement accounts for a considerable share of the variance of aggregate variables. However, little is known about its time-varying aspects by now. In this article, a multivariate DCC- GARCH framework is employed to study dynamics of sectoral comovement across manufacturing sectors both in the United States and in Germany. To account for possible nonlinearities, asymmetric effects in conditional volatilities as well as in conditional correlations are being assessed. We find that comovement across sectors is not stable but shows irregular movements. Particularly, contractions tend to be more synchronized than expansions in manufacturing sector. Moreover, we examine the role of various aggregate factors for the fluctuations in conditional correlations. Our findings reveal that both the non-constant variability of common factors and the changes in the effects of these factors play role for the fluctuations in sectoral comovement.     

Sectoral and Aggregate Technology Shocks:Is There a Relationship?

We analyze sector-specific shocks in productivity and demand in 19 manufacturing sectors of the Austrian economy. Based on a structural vector autoregressive model (SVAR) with long-run restrictions developed by Galí (1999) we extract technology and non-technology shocks from sectoral and aggregate data. We study their patterns and relationship by means of a principal components analysis and find a close association of sectoral and macroeconomic non-technology shocks but only a very weak association for technology shocks. Impulse response analysis indicates that for almost all manufacturing sectors as well as the aggregate Austrian economy productivity growth rates experience an immediate increase due to positive technology shocks while hours worked decline. Thereby we confirm Galís results on the level of Austrian manufacturing industries. From regression analysis, we find that our shocks are closely associated to employment growth and output growth but not to investment growth and that the reaction is different for the aggregate economy and manufacturing industries.JEL codes: D24, E23, E32, O30We thank Werner Müller and the participants of the 2004 conference of the Austrian Economic Association (NOeG) for helpful comments. We would like to thank an anonymous referee for many helpful comments that led to a substantial improvement of the paper. The usual disclaimer applies. This research project was supported by a research Grant (Project Nr. 9800) of the Jubiläumsfonds der Österreichische Nationalbank (OeNB).     

The impact of productivity and demand shocks on structural dynamics: Evidence from Austrian manufacturing

Based on Pasinetti's model of structural dynamics we develop an empirical identification strategy for aggregate and sectoral labor productivity and demand shocks in a structural vector autoregressive model with long-run restrictions. Impulse response analysis shows that we can distinguish four patterns of the effects of changes in demand and productivity growth on sectoral output growth. For some industries demand is indeed the factor driving sectoral growth. Labor productivity and demand shocks are closely associated with the growth rates of employment and output across industries. However, there is less correlation with entry and exit. This suggest that structural change within and between industries may have quite different determinants.     

Sectoral and aggregate technology growth in Spain

In this paper we analyze technological change in the Spanish economy by constructing adjusted Solow residuals, where the adjustment attempts to correct for the bias associated with the potential presence of imperfect competition, increasing returns, variable input utilization and, especially, sectoral reallocation of inputs across sectors. We refer to this modified Solow residual as a technology index. Sectoral reallocations and variable input utilization are key determinants of the differences between the aggregate Solow residual and the technology index resulting from the aggregation of estimated sectoral technological growth. We show that starting in the mid nineties, there has been a deceleration in the aggregate growth rate of technology which is basically due to the behaviour of the manufacturing sectors. Finally, our results imply that aggregate technology growth is less volatile than aggregate productivity as measured by the Solow residual.     

Must improved labor standards hurt accumulation in the targeted sector? Stylized analysis of a developing economy

This paper analyzes a stylized small open economy that consists of two tradable output-producing sectors: a manufacturing sector and a (mainly tourism-related) services sector. Assuming sectoral differences based on stylized facts, we explore the impact of higher labor standards in the manufacturing sector on the long-term prospects of the economy using comparative dynamic exercises to analyze changes in relative prices, foreign capital flows, and the sectoral distribution of investment and output. We find, in particular, that imposing higher standards across the manufacturing sector could, under certain conditions, shift the structure of the domestic economy in favor of that sector. This result is driven by changes in relative profitability in the presence of learning-by-exporting.     

A tale of two states: Maharashtra and West Bengal

In this paper we study the decline of West Bengal relative to Maharashtra, historically two of the most important states of India. In 1960, West Bengal's per capita income exceeded that of Maharashtra, the third richest state at the time. By 1993, it had fallen to just 69 percent of Maharashtra's per capita income. We employ a “wedge” methodology based on the first order conditions of a multi-sector neoclassical growth model to ascertain the output and factor market sources of the divergent economic performances. Our diagnostic analysis reveals that a large part of West Bengal's development woes can be attributed to: (a) low sectoral productivity, especially in manufacturing and services; and (b) sectoral misallocation in labor markets between the manufacturing sector and the other sectors of the economy. We also present evidence on the labor market, the manufacturing sector, and public infrastructure that suggest a systematic worsening of the business environment in West Bengal during this period.     

How important is the intermediate input channel in explaining sectoral employment comovement over the business cycle?

This paper investigates both analytically and quantitatively the role of intersectoral linkages in explaining sectoral employment comovement over the business cycle. We use a multisector dynamic stochastic general equilibrium model calibrated to the 2-digit SIC level intermediate input-use and capital-use tables and sectoral productivity shocks. With indivisible labor implying constant marginal utility of leisure, intersectoral linkages at the disaggregated level generate strong employment comovement across sectors. With divisible labor, however, procyclical marginal utility of leisure can dominate intersectoral linkages, implying some negative comovement. It further requires some form of the difficulty in reallocating labor across sectors, so that the substitutability of labor supply across sectors is relatively low. With divisible labor, a limited substitution of labor hours across sectors is shown to generate strong employment comovement over the business cycle.     

IS CORPORATE R&D INVESTMENT IN HIGH‐TECH SECTORS MORE EFFECTIVE?

This paper discusses the link between R&D and productivity across the European industrial and service sectors. The empirical analysis is based on both the European sectoral OECD data and on a unique micro‐longitudinal database consisting of 532 top European R&D investors. The main conclusions are as follows. First, the R&D stock has a significant positive impact on labor productivity; this general result is largely consistent with previous literature in terms of the sign, the significance, and the magnitude of the estimated coefficients. More interestingly, both at sectoral and firm levels the R&D coefficient increases monotonically (both in significance and magnitude) when we move from the low‐tech to the medium‐ and high‐tech sectors. This outcome means that corporate R&D investment is more effective in the high‐tech sectors and this may need to be taken into account when designing policy instruments (subsidies, fiscal incentives, etc.) in support of private R&D. However, R&D investment is not the sole source of productivity gains; technological change embodied in gross investment is of comparable importance on aggregate and is the main determinant of productivity increase in the low‐tech sectors. Hence, an economic policy aiming to increase productivity in the low‐tech sectors should support overall capital formation.     

Sectoral Energy- and Labour-Productivity Convergence

This paper empirically investigates the development of cross-country differences in energy- and labour productivity. The analysis is performed at a detailed sectoral level for 14 OECD countries, covering the period 1970–1997. A σ-convergence analysis reveals that the development over time of the cross-country variation in productivity performance differs across sectors as well as across different levels of aggregation. Both patterns of convergence as well as divergence are found. Cross-country variation of productivity levels is typically larger for energy than for labour. A β-convergence analysis provides support for the hypothesis that in most sectors lagging countries tend to catch up with technological leaders, in particular in terms of energy productivity. Moreover, the results show that convergence is conditional, meaning that productivity levels converge to country-specific steady states. Energy prices and wages are shown to positively affect energy- and labour-productivity growth, respectively. We also find evidence for the importance of economies of scale, whereas the investment share, openness and specialization play only a modest role in explaining cross-country variation in energy- and labour-productivity growth.      

Working hard in the wrong place: A mismatch-based explanation to the UK productivity puzzle

The UK experienced an unusually prolonged stagnation in labor productivity in the aftermath of the Great Recession. This paper analyzes the role of sectoral labor misallocation in accounting for this “productivity puzzle”. If jobseekers disproportionately search for jobs in sectors where productivity is relatively low, hires are concentrated in the wrong sectors, and the post-recession recovery in aggregate productivity can be slow. Our calculations suggest that, quantified at the level of three-digit occupations, this mechanism can explain up to two thirds of the deviations from trend-growth in UK labor productivity since 2007.     

Do technology shocks lower hours worked? – Evidence from Japanese industry level data

We examine the response of productivity and hours worked to technology and nontechnology shocks using the Japan Industrial Productivity (JIP) Database. We find that, at the aggregate level, positive technology shocks increase hours worked both in the manufacturing and the nonmanufacturing sector, accounting for a large fraction in the variances of hours worked. At the two- and three-digit industry levels, in contrast, we find that the correlation between productivity and hours worked in response to sectoral technology shocks tends to be negative. Further, we find that neither aggregate nor sectoral technology shocks appear to be the dominant factor underlying fluctuations in hours worked at the disaggregate level. The productivity decline in response to nontechnology shocks is not related to a permanent change in the relative size of industries.     

The structural transformation and aggregate productivity in Portugal

We document the substantial process of structural transformation—the reallocation of labor between agriculture, manufacturing, and services—and aggregate productivity growth undergone by Portugal between 1956 and 1995. We assess the quantitative role of sectoral labor productivity in accounting for these processes. We calibrate a model of the structural transformation to data for the United States and use the model to gain insight into the factors driving the structural transformation and aggregate productivity growth in Portugal. The model implies that Portugal features low and roughly constant relative productivity in agriculture and services (around 22%) and a modest but growing relative productivity in manufacturing (from 44 to 110%). We find that productivity growth in manufacturing accounts for most of the reduction of the aggregate productivity gap with the United States and that a further closing of this gap can only be accomplished via improvements in the relative productivity of services. This paper was written while the authors were affiliated with the Federal Reserve Bank of Richmond. We would like to thank the editor, two anonymous referees, and participants at the Third Conference on Portuguese Economic Development in the European Context organized by the Bank of Portugal for their comments. All errors are our own.     

THE IT REVOLUTION ACROSS THE UNITED STATES

In this paper we study the geography of the IT revolution in the U.S. economy. By relating the intensity of IT production and diffusion to labor productivity growth for the United States, we find three main results. First, states with above-average production intensity of IT manufacturing show more growth acceleration than other states. Second, the same applies to states with above-average IT diffusion. Yet, while the result for IT-producing states is strong, the result for IT-using states is somewhat smaller and less robust across specifications. Third, we also reconcile our state-wide pieces of evidence with previous industry and aggregate evidence. Accelerating productivity growth in IT-producing states stems from both IT-producing and IT-using industries in those states and is not a manifestation of the exclusive importance of IT production. Moreover, the less robust evidence for IT-using states is due to lower growth contributions from IT-producing and other industries in these states, not a symptom of a missing effect of IT usage.     

Heterogeneous productivity shocks,elasticity of substitution and aggregate fluctuations

We use a Dixit-Stiglitz setting to show that aggregate productivity fluctuations can be generated through changes in the dispersion of firms’ productivity. When the elasticity of substitution among goods is larger than one, an increase in the dispersion raises aggregate productivity because firms at the top of the distribution produce most of output. When the elasticity is smaller than one, an increase in the dispersion reduces aggregate productivity because firms at the bottom of the distribution use most of inputs. We use individual firm level data from Spanish manufacturing firms to test the relationship between the dispersion of firms’ productivity and aggregate productivity. The estimated coefficients are consistent with the predictions of the model: we find that an increase in the coefficient of variation of firms productivity of 1% increases aggregate productivity by 0.16% in sectors with an elasticity of substitution larger than one while the same increase in the standard deviation reduces aggregate productivity by 0.36% in sectors with an elasticity of substitution smaller than one.