Sectoral Productivity Growth Rates Research Articles

Sectoral labour reallocation: An agent-based model of structural change and growth

The shift of labour out of the agricultural sector and into the manufacturing and services sectors seems to be an important factor in explaining why some countries are so much richer than others. Therefore, understanding not only the driving mechanisms and forces behind the process of structural change but also how these mechanisms interact and reinforce each other becomes crucial. In the present work, we develop an agent-based model (ABM) where structural change is driven by income and relative prices effect. The income effect is generated by the assumption of a simple non-homothetic hierarchical demand structure where consumers spend their wealth following a particular priority ordering. The relative prices effect results from different sectoral productivity growth rates. The model is capable of theoretically replicating the dynamics of structural change where labour is reallocated across the three macro-sectors of agriculture, manufacturing and services. We have calibrated the model's parameters, so that the artificial employment share trajectories would match those of Sweden for the period of 1890–2010. The results suggest that, the income and relative prices effect are complementary in generating a process of structural change of the type experienced by developed economies. If some assumptions regarding agents’ behaviour and sectoral relative conditions are respected, the model shows that it possible to theoretically yield structural changes in an agent-based model focusing only on first principles such as tastes and technologies.

Vietnam: The next asian Tiger?

We investigate the growth experience of Vietnam, the country which has been getting recent attention as being the next emerging giant. First, we present an aggregate level investigation of Vietnam’s economic growth experience, since the inauguration of reform in 1986 known as Doi Moi. We focus on a top-down approach that performs growth and level accounting exercises. These decompositions offer the possibility to track the economic progress of Vietnam and to formulate policy accordingly depending on where the gaps originate from. Second, we build a two-sector general equilibrium model, investigating the secular decline in agricultural employment. Despite the notable structural changes over the past thirty years, agriculture still has a substantial weight in the Vietnamese economy. We conduct a quantitative analysis using a theoretical framework, with an emphasis on the counterfactual outcomes of inheriting Chinese sectoral productivity growth rates, where China is recognized as the paragon emerging economy. The main findings are: (i) Vietnam has grown impressively since 1986, but is still a relatively poor country in absolute terms; (ii) Vietnam must decrease its reliance on factor accumulation as its source of growth and increase its technological capabilities; (iii) economic policies should equally target both agricultural and nonagricultural sectors to increase sectoral productivity growth rates in Vietnam.

Productivity growth and labor reallocation: Latin America versus East Asia

Over the period 1963 to 2010, Latin American countries exhibit much slower de-agriculturalization than East Asian countries. The manufacturing employment share has been almost stagnant in Latin America, but exhibits a hump-shaped pattern in Korea and Taiwan. Both groups have moved increasingly toward service-based economies. A nine-sector general equilibrium model, treating sectoral productivity growth rates as exogenous, accounts for some of the differing sectoral allocations of employment in Latin America and East Asia over the sample period. I perform a series of experiments, replacing the sectoral labor productivity growth rates in each sector for each Latin American country with the corresponding growth rates in Korea and Taiwan. Low aggregate productivity growth in Latin America is an economy-wide phenomenon concerning all sectors; however, the findings highlight the possible importance of raising productivity in manufacturing and wholesale to have significant increases in aggregate productivity growth rates. I focus attention on the importance of the level of disaggregation in examining the relationship between labor productivity growth and sectoral movement of labor. Some evidence is presented in linking sectoral policies to productivity growth in Latin America and East Asia.

Decompositions of productivity growth into sectoral effects

The paper provides some new decompositions of labour productivity growth and Total Factor Productivity (TFP) growth into sectoral effects. These new decompositions draw on the earlier work of Tang and Wang (2004). The economy wide labour productivity growth rate turns out to depend on the sectoral productivity growth rates, output price effects and changes in sectoral labour input shares. The economy wide TFP growth decomposition is similar but some extra terms due to input price inflation make their appearance in the decomposition.

Increasing Share of Agriculture in Employment in the Time of Crisis: Puzzle or Not?

In the first quarter of 2008, along with the beginning of the crisis, the employment share of agriculture in Turkey deviated from its long-run trend and started to rise. Both the timing and the direction of the change caused a public debate seeking an explanation of this phenomenon. Getting attention in the debate is the fact that labor productivity in agriculture has been declining since that quarter. How much of the increase in agricultural employment can be explained by the secular changes in its productivity? To answer this question, we use a multi-sector general equilibrium model in which employment share in agriculture is determined solely by the subsistence constraint and labor productivity in agriculture, where sectoral productivity growth rates are treated as exogenous. The model accounts for more than 90 percent of the decline in the agricultural employment share between 2000:Q2 and 2010:Q3. The model is also able to generate the increase in agricultural employment since 2008:Q1, although it slightly overpredicts the agricultural employment share. The model also predicts the sectoral allocations of labor in non-agricultural activities during the sample period. A detailed analysis of the driving forces of the growth in agricultural productivity is needed, since it lies at the heart of the secular changes in employment shares in Turkey.

Engel versus Baumol: Accounting for structural change using two centuries of U.S. data

In the last two centuries, the reallocation of labor out of agriculture has been a dominant feature of structural change and economic growth in the United States. This paper uses an accounting framework founded in economic theory to decompose this reallocation into three components: a demand-side effect due to the low income elasticity of demand for agricultural goods (Engel effect), and two supply-side effects, one due to differential sectoral productivity growth rates (Baumol effect), and the other to differential capital deepening. The results show that the Engel effect accounts for almost all labor reallocation until the 1950s, after which the Baumol effect becomes a key determinant. Our framework provides a unified account of long-run structural change, and demonstrates that historical interpretations and theoretical models that emphasize only one dimension of this process cannot properly account for the dramatic history of labor reallocation in the United States.

Comments and Discussion

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...

International Trade and Productivity Growth: Exploring the Sectoral Effects for Developing Countries

The paper estimates an empirical relation based on Krugman's "technological gap" model to explore the influence of the pattern of international trade and production on the overall productivity growth of a developing country. A key result is that increased import competition in medium-growth (but not in low- or high-growth) manufacturing sectors enhances overall productivity growth. The authors also find that a production-share weighted average of (technological leaders') sectoral productivity growth rates has a significant effect on the rate of aggregate productivity growth. Copyright 2000, International Monetary Fund

Telecommunications and growth: The contribution of telecommunications infrastructure investment to aggregate and sectoral productivity

Given the weakening economic performance of the USA in recent years, productivity growth has become increasingly the focus of discussions by policy makers at both the federal and state level. While much attention has been directed towards the institutional and social causes underlying stagnant productivity levels, little effort has been given to identifying and measuring the factors that have consistently contributed to the nation's productivity over recent historical periods. For example, industry-specific advancements that not only affect a sector's own productivity but permeate the economy can contribute to overall national productivity. This is the case with telecommunications. The empirical findings in this study suggest that investment in telecommunications infrastructure is causally related to the nation's total factor productivity and that contributions to aggregate and sectoral productivity growth rates from telecommunications advancements are both quantifiable and substantial.

PRODUCTIVITY GROWTH IN AGRICULTURE (REVISITED): A MEASUREMENT FRAMEWORK AND SOME EMPIRICAL RESULTS

This paper explores the methodology of sectoral productivity growth measurement within the framework of input‐output analysis. A method which ensures that sectoral productivity growth rates are consistent with productivity growth rates for the economy as a whole (as well as allowing for external trade) is suggested. New estimates are presented on total factor productivity in UK agriculture using a Tornqvist index procedure. In addition, new estimates of agricultural labour productivity growth are presented, taking account not only of labour employed in agriculture but also of labour employed in ancillary industries on the supply side. The empirical results confirm that part of the labour previously employed on farms has shifted “upstream” to industries providing agriculture with fertilises, machinery and other inputs.