The Sources of Productivity Slowdown in Pakistan: A Novel Structural Decomposition Analysis

Concerns about Canada’s lackluster productivity growth have made it a priority on the public policy agenda. In this paper we argue that we should not automatically interpret declines, or slower growth rates, in aggregate labour productivity as deterioration in living standards because changes in an economy’s terms of trade are also important. Low rates of productivity growth may be the result of welfare improving changes in a country’s terms of trade that shift labour to sectors with declining labour productivity. We use the Generalized Exactly Additive Decomposition (GEAD) procedure to show how 15 sectors have contributed to aggregate business sector productivity growth in Canada from 1997 to 2019. This procedure separates a sectors’ contributions to aggregate productivity growth through relative output price changes, as well as within-sector labour productivity effects and labour reallocation effects. This analysis shows that labour productivity in Canada’s business sector increased by 30.7 percent between 1997 and 2019, an average annual growth rate of 1.2 percent. Finance, Insurance, and Real Estate (FIRE) made the largest contribution to aggregate labour productivity growth and followed by the Mining, Oil and Gas Extraction sector. The only sector that made a negative contribution to aggregate productivity growth was Manufacturing because of declines in the relative price of manufactured goods and the sector’s share of total labour input. Panel regression models indicate that a change in relative prices can indirectly influence a sector’s output per hour through changes in labour inputs. In three resource-based sectors and five service sectors, labour productivity declines when its share of labour input increases in a given year.

Comment

Structural change and economic growth in India

Relevance. Economic growth can be achieved in two different ways: through technological improvements and reallocation of market shares from less to more productive units. Despite the significant research literature on innovation in Russia, the literature on market selection, especially at the sectoral level, is relatively scarce. This is the research gap that this study aims to address. Research objective. The article assesses how labor resource reallocation between sectors has influenced the dynamics of aggregate labor productivity in the Russian economy over the past two decades. Data and methods. For this purpose, the growth of aggregate labor productivity was decomposed into the growth of productivity within the sectors themselves and the reallocation of labor resources between them. This allowed us to conduct a quantitative estimation of the role of market selection at the sectoral level. For our study, we used data from Rosstat (from 2002 to 2018) and the World Input-Output Database (from 2000 to 2014). Results. For Rosstat data, the ratio of the effect of changes in labor productivity and labor resource reallocation by sector on total labor productivity over the period was 0.71/0.29, and for WIOD data it was 0.44/0.56. This indicates that labor resources are more likely to be reallocated to related sectors (e.g. between manufacturing industries). Conclusions. The results suggest that there is competitive market selection at the sectoral level and that labor has generally been reallocated to more productive sectors of the economy, contributing significantly to the growth of aggregate productivity in the economy. Our study shows the sectors of the economy where this reallocation has taken place, which may help to determine where this process is successful and where it needs additional stimulation.

Structural transformation and productivity growth in India during 1960–2010

Comment

ABSTRACTThe paper uses the World Input-Output Database to address patterns of structural transformation in BRIC countries, Indonesia, South Korea, Mexico and Turkey. Sectoral drivers of aggregate labour productivity growth, and the relative importance of within-sector versus employment reallocation effects on aggregate labour productivity growth, are evaluated using growth accounting decomposition methods. Decomposition results are used to assess how patterns of structural transformation relate to macroeconomic performance in terms of aggregate labour productivity, output and employment growth. Together with the construction of ‘Hirschman compliance indices’, decomposition results are also used to shed light on the balanced versus unbalanced growth debates. The paper goes on to assess the extent of complementarities between manufacturing and information and communications technology-intensive advanced services through intermediate inputs, comparing the eight emerging countries with G7 countries over time.

Title of dissertation: ESSAYS ON THE ECONOMETRIC ANALYSIS OF U.S. AGRICULTURE Shinsuke Uchida, Doctor of Philosophy, 2014 Dissertation directed by: Professor Erik Lichtenberg Department of Agricultural and Resource Economics This dissertation consists of three essays empirically investigating three important aspects of the U.S. agriculture: conservation, subsidy, and productivity. Each essay is conducted with the U.S. Census of Agriculture micro file data. Availability of cross-sectional and time variations of detailed individual farm production and demographic characteristics allows for uncovering heterogeneous relationships between farm production decisions and the corresponding aspects of U.S. agriculture. The first essay examines an adverse effect of a cropland retirement policy. A cropland retirement policy contributes to the reduction of environmental externalities from agricultural production such as soil erosion, nutrient runoff and loss of wildlife habitat. On the other hand, participant’s potential adverse behavior could undermine the environmental benefits of the policy. Several sources of such an unintended effect, known as “slippage”, have been conceptually identified, but their empirical evidence has been scarce. This article tests one source of slippage caused by in-farm land substitution from noncropland to cropland as a result of farmland retirement in the U.S. Conservation Reserve Program (CRP). The causal relationship of CRP participation and subsequent slippage through in-farm land substitution is identified by employing farm fixed effects, time-varying county fixed effects, and selection-on-observables. These could eliminate effects of unobservables that are potentially correlated with both the program participation and subsequent farmland reallocation decisions. Overall, slippage seems evident and fairly robust among specifications. It is found that an average program participant converts 14% of noncropland to cropping activities after enrollment. Results further show that participants with a larger share of uncropped land contribute more to slippage, indicating that farms with the excess capacity of conversion are more flexible in the land allocation decision and thus likely to give rise to slippage. This suggests that additional restrictions on the rest of land use for participants and/or introduction of penalty points reflecting the share of noncropland in the current auction mechanism can hinder such a backward incentive offsetting the program benefits. The second essay examines the distortionary effects of agricultural policy on farm productivity by examining the response of U.S. tobacco farmers’ productivity to the quota buyout of 2004. We focus on the impact of distortionary policy, i.e., the tobacco quota, by decomposing aggregate productivity growth into the contribution of farm-level productivity growth and the contribution of reallocation of resources among tobacco growers. We find that the aggregate productivity of Kentucky tobacco farms grew 44% between 2002 and 2007. The elimination of quota rental costs and reallocation of resources, including entry and exit, accounted for most of the post-buyout productivity growth. It is also noted that the aggregate productivity of Kentucky tobacco farms vary across farm characteristics and locations. This highlights the importance of using highly disaggregated data to uncover the sources of aggregate productivity growth. The third essay examines the relationship between farm size and productivity growth. In the past several decades, crop production in the U.S. has shifted to larger farms. During the same period, crop productivity has fairly improved. While these two events seem clearly associated, no studies have fully uncovered the link between them. Using farm-level longitudinal data from the Censuses of Agriculture from 1987-2007 enables us to decompose the contributions of aggregate productivity growth (APG) by farm size, but also by farm entry/exit and by technology/reallocation. We have three main findings. First, productivity growth is clearly non-uniform among farm sizes. Between 1987 and 2007, virtually all of the aggregate productivity growth of crop farms came from farms with annual sales of more than $500,000. These farms account for only 8% of U.S. crop farms. A closer look at the APG contributions to productivity growth from surviving farms confirms the findings for all crop farms: the productivity of mid-size farms has barely increased, and the productivity of smaller farms has fallen. Finally, the relative importance of technical efficiency growth and resource reallocation varies over time. Technical efficiency growth seems to be a larger source of APG for large farms between 1987 and 1997, whereas reallocation across all sales classes contributes more to APG between 1997 and 2007. Overall, our finding provides the concrete evidence that farm consolidation has been strongly associated with the productivity growth of U.S. crop farms. Our finding that resource reallocation through farm consolidation is nontrivial for the APG of crop farms highlights the usefulness of farm-level panel data for studying structural changes and APG. ESSAYS ON THE ECONOMETRIC ANALYSIS OF U.S. AGRICULTURE

This study decomposes aggregate labor productivity growth in Turkey from 1999 to 2023 using a chain-linked gross domestic product (GDP) series with an exactly additive decomposition method. Traditionally, this growth has been decomposed into two components: productivity growth within sectors and labor reallocation across sectors. Using the chain-linked GDP series introduces a third component: changes in relative sectoral prices. Although these relative price changes cancel out at the aggregate level, they influence sectoral contributions to overall labor productivity by altering each sector’s weight in total output. Incorporating them, therefore, provides a more comprehensive view of sectoral dynamics by capturing their contributions to aggregate productivity growth. On average, the contribution of structural change slightly exceeds that of the within component. However, both the magnitude and composition of contributions vary considerably across sub-periods. During crisis years, structural change contributed positively while the within-sector component was negative. In contrast, during non-crisis periods, aggregate labor productivity growth declined because the structural-change component weakened persistently and nearly vanished after 2018, despite a positive though limited within-sector component. At the sector level, construction, finance and real estate, community, personal, and government services, and transport and communication largely account for the slowdown, while manufacturing’s contribution stayed steady; its composition shifted away from within productivity across periods.

Aggregate labor and multifactor productivity growth slowed substantially post‐2000 in the Canadian manufacturing sector. To examine the source of the decline, this paper proposes a decomposition method that delves deeper into the two micro‐components of aggregate productivity growth: a within‐plant component and a between‐plant component. The decomposition builds on earlier work by Jorgenson and his collaborators that decomposes aggregate productivity growth into its industry components, but applies it to the plant level and introduces non‐neoclassical features of the plant‐level economic environment. It finds that the preponderance of the aggregate labor and multifactor productivity growth slowdown is due to the pro‐cyclical nature of productivity growth arising from capacity utilization. Almost all of the aggregate productivity growth slowdown is driven by exporters, as exporters experienced large declines in labor productivity growth in the post‐2000 period as a result of large declines in their capacity utilization.

Export Growth, Capacity Utilization and Productivity Growth: Evidence from Canadian Manufacturing Plants

Productivity - the efficiency with which firms transform inputs into outputs - is the root of economic growth and the improvement of living standards. This thesis explores different financial frictions that affect productivity at the corporate level and their aggregate consequences. The first chapter, “Credit Market Frictions and the Productivity Slowdown”, is joint work with John Van Reenen and Timothy Besley. UK labour productivity growth has been particularly weak since the financial crisis. We develop a theoretical framework to quantitatively assess the magnitude of financial frictions and their impact on aggregate productivity. We apply this framework to administrative panel data on UK firms. The approach highlights a firm’s default probability as a sufficient statistic for frictions. We use Standard and Poor’s PD Model algorithm to measure market participants’ perceptions of firm-specific default risk. The theoretical framework suggests an aggregate measure of market inefficiency which we show can be applied to UK administrative panel data to explain how far the dramatic productivity slowdown in the wake of the crisis is due to market frictions. We find that frictions cause a loss of 7% to 9% of GDP on average per year in 2004-12. These frictions increased during the crisis and lingered thereafter accounting for between one-quarter and one-third of the productivity fall in 2008-2009 and of the gap between actual and trend productivity by the end of 2012. The second chapter, “Management practices, precautionary savings, and company investment dynamics”, investigates a potential channel behind the well-documented positive correlation between the quality of management practices and firm performance. The main hypothesis of the paper is that financially constrained firms accumulate larger cash reserves when they are better managed. This allows them to avoid the costs of underinvestment when future profitable investment opportunities arise. The theoretical analysis predicts that well managed firms which face financial constraints save relatively more out of their cash flows and accumulate more cash when their cash flows are more volatile. This enhanced precautionary behaviour arises because management quality alleviates agency problems between equity holders and managers. The empirical analysis provides evidence to support these predictions using data from the World Management Survey and administrative and accounting data on UK firms. A direct consequence of this enhanced precautionary behaviour is that well managed firms invest more efficiently. Specifically, they adjust more quickly towards their long-run equilibrium capital stock when their current capital stock falls short of the latter. The paper provides evidence of this using a dynamic model of investment. The third chapter, “When Does Leverage Hurt Productivity Growth? A Firm-Level Analysis”, is joint work with Fabrizio Coricelli, Nigel Driffield, and Sarmistha Pal. Following the global financial crisis, several macroeconomic contributions have highlighted the risks of excessive expansion. In particular, too much finance can have a negative impact on growth. We examine the microeconomic foundations of this argument, positing a non-monotonic relationship between leverage and firm-level total factor productivity (TFP) growth. A threshold regression model estimated on a sample of Central and Eastern European countries confirms that TFP growth increases with leverage until the latter reaches a critical threshold beyond which leverage lowers TFP growth. We find similar non-monotonic relationships between leverage and proxies for firm value. The fourth chapter, “The sullying effect of sclerosis on productivity”, explores the impact of depressed flows on productivity in a partial equilibrium search and matching model of the banking market. Reputational costs associated with the termination of lending relationships drive a wedge between rates on new and existing loans. This induces misallocation of capital across borrowers. The phenomenon is one of credit sclerosis: Low-productivity firms are kept alive through subsidised loan rates, while high-productivity entrants face an inefficiently high cost of borrowing and limited supply of new loan facilities. As a consequence, too much is allocated to old firms. Aggregate labour productivity and TFP are reduced. The model also sheds some light on why a policy tool like the UK’s Funding for Lending Scheme might fail to revive productivity in the presence of costly loan termination.

Productivity Growth and the New Economy William D. Nordhaus What, another paper on the new economy? When financial markets are raking through the debris of $8 trillion in lost equity value, and ".com" is a reviled four-symbol word, a paper on the impact of the new economy on productivity would seem as welcome as an analysis of the role of whales in the lighting revolution. In fact, the new economy (or, more precisely, information technologies) continues to raise important puzzles about productivity growth. Variations in productivity growth have proved to be one of the most durable puzzles in macroeconomics. After a period of rapid growth following World War II, productivity stagnated in the early 1970s. There was no shortage of explanations offered, including rising energy prices, high and unpredictable inflation, rising tax rates, growing government, burdensome environmental and health regulation, declining research and development, deteriorating labor skills, depleted possibilities for invention, and societal laziness.1 Yet these explanations seemed increasingly inadequate as inflation fell, tax rates were cut, regulatory burdens stabilized, government's share of output fell, research and development and patents granted grew sharply, real energy prices fell back to pre-1973 levels, and a burst of invention in the new economy and other sectors fueled an investment boom in the 1990s. The productivity slowdown puzzle of the 1980s evolved into the Solow paradox of the early 1990s: computers were everywhere except in the [End Page 211] productivity statistics. The penetration of the American workplace by increasingly sophisticated and powerful computers and software apparently failed to give an upward boost to productivity growth, for through thin and thick, labor productivity growth seemed to be on a stable track of slightly over 1 percent a year. Then, in the mid-1990s, productivity growth rebounded sharply. Beginning in 1995, productivity in the business sector grew at a rate close to that in the pre-1973 period. The causes of the rebound were widely debated, but at least part was clearly due to astonishing productivity growth in the new economy sectors of information technology and communications. This period led to yet another paradox, identified by Robert Gordon, who argued that, after correcting for computers, the business cycle, and changes in measurement techniques, there was no productivity rebound outside the computer industry. This paper attempts to sort out the productivity disputes by using a new technique for decomposing sectoral productivity growth rates and using a new data set that relies primarily on value added by industry. In addition to examining the recent behavior of productivity, the paper adds a few new features to the analysis. First, it lays out a different way of decomposing productivity growth, one that divides aggregate productivity trends into factors that increase average productivity growth through changes in the shares of different sectors. Second, it develops an alternative way of measuring aggregate and industrial productivity based on industrial data built up from the income side rather than the product side of the national accounts. By relying on the industrial data, I can focus on different definitions of output and get sharper estimates of the sources of productivity growth. Third, by working with the new industrial data, I can make more accurate adjustments for the contribution of the new economy than has been possible in earlier studies. Finally, this new data set allows creation of a new economic aggregate, which I call "well-measured output," that excludes those sectors where output is poorly measured or measured by inputs. Productivity Accounting Measuring productivity would appear to be a straightforward issue of dividing output by inputs. In fact, particularly with the introduction of [End Page 212] chain-weighted output measures, disentangling the different components of productivity growth has become quite complex. In this section I explore how to decompose productivity growth into three components: a fixed-weight aggregate productivity index, a "Baumol effect" that reflects the effect of changing shares of output, and a "Denison effect" that reflects the effect of differences between output and input weights.2 Consider indexes for the major aggregates. Define aggregate output as Xt, composite inputs (here, hours of work) as St, and aggregate productivity as At = Xt/St. The share...

The paper uses accounting methods to decompose aggregate labour productivity and employment growth into their sectoral components as well as into within-sector and employment reallocation effects for a sample of 81 developed and developing countries using data going back to the mid-1980s. Key findings are that aggregate labour productivity growth for developing countries taken together is driven as much by services as by industry, in spite of strong differences between countries, and that within-sector effects on aggregate labour productivity growth are more important than employment reallocation effects, a pattern that holds for all regions.

Structural change and productivity growth in Europe — Past, present and future