This paper constructs a theory of industry growth to study the implications of knowledge diffusion and selection for innovation policy. Firms’ ideas determine their productivity and stochastically evolve over time. Firms innovate to improve their ideas and endogenously exit if unsuccessful. Entrants adopt the ideas of incumbents. In this model, creative destruction operates through selection: when better ideas are innovated or adopted, they selectively replace worse ideas. Innovation externalities vary based on firm productivity: ideas generated by more productive firms create 1) longer-lasting positive externalities due to knowledge diffusion and 2) stronger negative externalities due to dynamic competition effects. Therefore, the net external effect of innovation is heterogeneous across firms. Quantitatively, this heterogeneity is large when the model is calibrated to firm-level data from US manufacturing and retail trade, and implies first-order considerations for the design of innovation policy.
We present a new multi-sector growth model that accommodates long-run demand and supply drivers of structural change. The model generates nonhomothetic Engel curves at all levels of development and is consistent with the decline in agriculture, the hump-shaped evolution of manufacturing and the rise of services over time. The economy converges to a constant aggregate growth rate that depends on sectoral income elasticities, capital intensities and rates of technological progress. We estimate the demand system derived from the model using historical data on sectoral employment shares from twenty-ﬁve countries and household survey data from the US. Our estimated model parsimoniously accounts for the broad patterns of sectoral reallocation observed among rich, miracle and developing economies in the post-war period. We ﬁnd that income eﬀects play a major role in generating structural change.
This paper studies the demand-side forces that determine the direction of firms’ research and development investments. We develop a multi-sectoral endogenous growth model in which the direction of innovation across sectors is endogenous. The model provides a theoretical framework for studying the classical demand-pull versus technology-push drivers of innovation in a general equilibrium setting. A robust prediction is that innovation growth should be higher in more income- elastic sectors. We test this prediction using the universe of U.S. patents and firm R&D investments for the period 1976-2007. The analysis lends empirical support for the main predictions of the model.
Micro-level studies robustly document heterogeneity in price and income elasticity of goods produced by different industries or firms. However, this heterogeneity is absent from most theories of aggregate and macro-level phenomena. In this paper, we provide a flexible yet tractable general-equilibrium framework for the study of heterogeneity in price and income elasticity across goods. We first show that a broad class of demand systems that either focus on price or income elasticity heterogeneity implicitly impose strong restrictions on the correlation between income and price elasticities across goods. We show that data on trade flows does not support such correlations for import demand. We provide a generalization of the standard CES preferences that flexibly allows for general patterns of correlations between income and price elasticity. As an application of our demand system, we embed it in a Ricardian model of international trade and show it implies intuitive corrections to the standard results for the welfare gains from trade. These corrections stem from the fact that the gains from access to new varieties strongly hinge on the price and income elasticity composition of the traded goods. Empirically, we show that these compositional effects result in substantially higher welfare gains from trade in rich relative to poor countries.
There has been a long-standing debate around the effectiveness of ex ante (push) incentives or ex post (pull) incentives in spurring innovation. In this paper, I study government untargeted fiscal R&D incentives. I show that if firms are heterogeneous in their capacity for innovation but the social planner can only observe their success or failure ex post, the optimal mechanism involves combining both ex ante and ex post incentives. More specifically, I find that under certain conditions optimal ex ante and ex post subsidies have the same size but are in reverse directions. In other words, the government should optimally tax (or subsidize) R&D investment and simultaneously subsidize (or tax) profits reaped from successful innovation. My theory includes two sources of private information, first regarding the entrepreneurs’ capacity for innovation and second, hidden choice of innovative efforts. I fully characterize the optimal policies in terms of parameters that may be empirically estimated from the data and can be applied in the design of R&D tax credits.