Structural transformation refers to the reallocation of economic activity across the broad sectors agriculture, manufacturing and services. This review article synthesizes and evaluates recent advances in the research on structural transformation. We begin by presenting the stylized facts of structural transformation across time and space. We then develop a multi-sector extension of the one-sector growth model that encompasses the main existing theories of structural transformation. We argue that this multi-sector model serves as a natural benchmark to study structural transformation and that it is able to account for many salient features of structural transformation. We also argue that this multi-sector model delivers new and sharper insights for understanding economic development, regional income convergence, aggregate productivity trends, hours worked, business cycles, and wage inequality. We conclude by suggesting several directions for future research on structural transformation.

We assess the empirical importance of income and relative price effects for structural transformation in the postwar US. We explain how there are two natural approaches to connect models of structural transformation to the data: sectors may be categories of final expenditure or value added; for example, the service sector may be the final expenditure on services or the value added from service industries. We estimate preferences for each approach and find that with final expenditure categories income effects are the dominant forces behind structural transformation whereas with value added categories relative price effects are dominant. We show how the input-output structure of the US economy can reconcile these different findings.

Structural transformation-i.e., the reallocation of resources across the broad economic sectors agriculture, manufacturing, and services-is a prominent feature of economic development. Kuznets (1966) included it as one of the main stylized facts of development, and recent work shows that extending the standard one-sector growth model to incorporate structural transformation is important for a variety of substantive issues.1 However, there remains no consensus on the economic forces that drive the process of structural transformation. Recent theories stress two distinct economic 1 See, for example, Laitner

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in February 2008 AbstractMany applications in economics use multi-sector versions of the growth model. In this paper, we measure the income shares of capital and labor at the sectoral level for the U.S.economy. We also decompose the capital shares into the income shares of land, structures, and equipment. We find that the capital shares differ across sectors. For example, the capital share of agriculture is more than two times that of construction and more than 50% larger than that of the aggregate economy. Moreover, agriculture has by far the largest land share, which mostly explains why it has the largest capital share. Our numbers can directly be used to calibrate standard multi-sector models. Alternatively, if one wants to abstract from differences in sector capital shares, our numbers can be used to establish that this is not crucial for the results.Keywords: input-output tables; industry-by-commodity total requirement matrix; sector factor shares JEL classification: O41; O47 * We thank the editor Tim Kehoe and two anonymous referees for suggestions that improved the paper considerably. We thank Edward Prescott for many helpful discussions about input-output tables, Randal Konoshita from the BLS for providing us with additional data, and Ben Bridgman, Cara McDaniel, Paul Schreck, and the audiences at ASU and the Federal Reserve Bank of Minneapolis for comments. Számos közgazdasági munka a neoklasszikus növekedési modell több szektoros változatát használja. Ebben a tanulmányban a tőkeés a munka szektor szintű jövedelemrészesedését mérjük az EgyesültÁllamokra. A tőke jövedelem részesedét felbontjuk föld,épületekés gépek részesedésére. Munkánk során azt találtuk, hogy a tőke részesedése jelentősen különbözik szektorok között. Például, a tőke részesedése a mezőgazdaságban több mint kétszer akkora, mint azépítőiparbanés 50%-kal magasabb, mint a gazdaság egészében. Számaink közvetlenül felhasználhatóak a több szektoros modellek paramétereinek kalibrálására. Ha pedig valaki el akar vonatkozatni a tőke jövedelemrészesedésének szektorok közötti különbségétől, akkor számaink felhasználhatók annak megállapítására, hogy ez lényeges-e vagy sem.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract This paper assesses the importance for structural transformation of three features of sectoral technology: labor-augmenting technological progress, capital intensity, and substitutability between capital and labor. We estimate CES production functions for agriculture, manufacturing, and services on postwar US data and compare them with Cobb-Douglas production functions with different and with equal capital shares. We find that sectoral differences in labor-augmenting technological progress are the main force behind the trends in observed relative prices and sectoral labor. As a result, sectoral Cobb-Douglas production functions with equal capital shares (which by construction abstract from differences in the elasticity of substitution and in capital shares) do a good job of capturing the postwar US structural transformation. Terms of use: Documents in

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Why is Measured Productivity so Low in Agriculture? Terms of use: Documents in EconStor may AbstractIn poor countries, labor productivity in agriculture is considerably lower than in the rest of the economy. We assess whether this well known fact implies that labor is mis-allocated between the two sectors. We make several observations that suggest otherwise. First, the same fact holds for US states where severe mis-allocation is implausible. Second, the gaps between the marginal value products of agriculture and non-agriculture are considerably smaller when measured through wages than through labor productivities. Third, labor productivity in agriculture is severely mis-measured in the US.JEL-Code: O100.

We document for 13 countries ranging from rich (Canada, United States) to poor (India, Indonesia) that average wages are considerably lower in agriculture than in the other sectors. Moreover, agriculture has less educated workers and lower Mincer returns. We view these findings through the lens of a multi-sector model in which workers differ in observed and unobserved characteristics and sectors differ in their human-capital intensities. We derive expressions for the implied barriers to the reallocation of labor out of agriculture. We find that in our sample these barriers are considerably smaller than what the macro-development literature has argued. (JEL J24, J31, J43, O13, O15, Q10)

We provide evidence on household and market production in 36 countries since 1960. On average the household sector accounts for almost half of total hours worked. As GDP per capita increases, the employment share of household production in total hours worked initially declines and then hardly changes while the employment shares of market goods and services decrease and increase. Estimating the value added of household production yields similar patterns. Labor productivity of household production is lower than and positively correlated with that in the market. These findings can be used as an input into quantitative work involving household production.