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We assess the empirical importance of changes in income and relative prices for structural transformation in the postwar United States. We explain two natural approaches to the data: sectors may be categories of final expenditure or value added; e.g., 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 income effects are the dominant force behind structural transformation, whereas with value-added categories price effects are more important. We show how the inputoutput structure of the United States can reconcile these findings.

We assess how the properties of technology affect structural transformation, i.e., the reallocation of production factors across the broad sectors of agriculture, manufacturing, and services. To this end, we estimate sectoral constant elasticity of substitution (CES) and Cobb-Douglas production functions on postwar US data. We find that differences in technical progress across the three sectors are the dominant force behind structural transformation whereas other differences across sectoral technology are of second-order importance. Our findings imply that Cobb-Douglas sectoral production functions that differ only in technical progress capture the main technological forces behind the postwar US structural transformation.

The structural-change literature typically assumes that investment is produced in manufacturing. We establish that this assumption is counterfactual: in the postwar U.S., the share of services value added in investment expenditure has been steadily growing. We develop a new model that features structural change in investment and consumption, characterize its equilibrium properties, and provide empirical support for it. We establish that modelling structural change in investment leads to three novel insights: constant TFP growth in all sectors is inconsistent with the existence of aggregate balanced growth with structural change; the sector with the slowest TFP growth absorbs all resources asymptotically; technical change is endogenously investment-biased.

Which sectors are most responsible for the low total factor productivities of developing countries? To answer this question we develop a new framework for sectoral development accounting. Applying this framework to the Penn World Table, we find that in equipment, construction, and food the sectoral TFP differences between developing countries and the United States are much larger than in the aggregate. However, in manufactured consumption the sectoral TFP differences are about equal to the aggregate TFP differences, and in services they are much smaller. We show that our level of disaggregation allows us to reconcile the results of existing studies of sectoral productivity differences, which have focused on noncomparable two-sector decompositions of the aggregate data. We also show that our results help shed light on existing theories of aggregate TFP differences.

We revisit the Kaldor growth facts for the United States and the United Kingdom during the postwar period. We find that while overall the original Kaldor facts continue to hold, deviations occurred along several dimensions: Instead of staying constant, the growth rates of real GDP per worker and of real capital per worker have slowed down in the United States and the United Kingdom since the 1970s, the capital-to-output ratio has increased in the United Kingdom, and the share of income paid to labor has decreased in the United States since 1990. We discuss how to calculate the Kaldor facts in multi-sector growth models and establish that a slowdown in GDP-per-worker growth naturally results from secular changes in relative prices. (JEL O41, O47)

It is well known that economies of scale that are external to the individual decision makers can lead to self-fulfilling prophecies and the multiplicity or even indeterminacy of equilibrium. We argue that the importance of this source of multiplicity and indeterminacy is overstated in representative agent models, as they ignore the potential stabilizing effect of heterogeneity. We illustrate this in a version of Matsuyama's (1991) two-sector model with increasing returns to scale. Two main results are shown. First, sufficient homogeneity with respect to individual productivity leads to the instability and non-uniqueness of a given stationary state and the indeterminacy of the corresponding stationary state equilibrium. Second, sufficient heterogeneity leads to the global saddle-path stability and the uniqueness of a given stationary state and the global uniqueness of equilibrium.

In a local interaction game agents play an identical stage game against their neighbours over time. For nearest neighbour interaction, it is established that, starting from a random initial configuration in which each agent has a positive probability of playing the risk dominant strategy, a sufficiently large population coordinates in the long-run on the risk dominant equilibrium almost surely. Our result improves on Blume (1995), Ellison (2000), and Morris (2000) by showing that the risk dominant equilibrium spreads to the entire population in a two dimensional lattice and without the help of mutation, as long as there is some randomness in the initial configuration.

It is well known that economies of scale that are external to the individual decision makers can lead to self-fulfilling prophecies and the multiplicity or even indeterminacy of equilibrium. We argue that the importance of this source of multiplicity and indeterminacy is overstated in representative agent models, as they ignore the potential stabilizing effect of heterogeneity.

In a local interaction game agents play an identical stage game against their neighbors over time. It is shown that a large population with only local interaction exhibits a strong tendency to coordinate on the risk dominant equilibrium even in the absence of mutation.