Endogenous Technical Change Research Articles

Relocation or reallocation: Impacts of differentiated energy saving regulation on manufacturing industries in China

Unilateral tightening of environmental regulation is often considered to cause regulated industries to locate at places with lower compliance cost. The pollution haven effect may be offset, however, when endogenous technical change and factor reallocation can compensate increased compliance cost. This paper identifies the overall effects on industrial activities from provincially differentiated regulation of energy saving in China. Econometric specifications take into account the workings of different policy instruments, quantity and revenue-based measurement of output, policy-induced price effects, and alternative measurement of productivity and competitiveness. Results indicate that an introduction of energy-saving policies leads to loss of output and productivity in energy-intensive industries initially, which is passed on to other industries via markets of capital and energy-intensive goods. Under higher regulation, energy-intensive industries become more capital-intensive, regain productivity more quickly, and increase export rates; other industries become more labor-intensive, recover more slowly, and decrease export rates. Through capital investment and factor reallocation, China's policy has been effective in improving industrial energy efficiency without causing competitive loss or carbon leakage. An incentive-based instrument of differential electricity prices leads to similar effects on industries, implying the possibility for more efficient policy-making.

Induced Innovation, Endogenous Technical Change and Income Distribution in a Labor‐Constrained Model of Classical Growth

AbstractWe present a steady state analysis of a labor‐constrained classical growth model with endogenous direction and intensity of technical change. Firms use retained profits to raise their productive capacity and to improve labor and capital productivities. Investments are planned to maximize instantaneous profits. Comparative dynamics exercises show that (1) an increase in the saving rate and in R&D subsidies raises the steady state labor share, labor productivity growth and the employment rate, and (2) a rise in workers' bargaining power reduces the employment rate while leaving productivity growth and distribution unaffected.

Spill or leak? Carbon leakage with international technology spillovers: A CGE analysis

This paper studies the effect of endogenous technical change and international technology spillovers on carbon leakage. It is well known that a unilateral CO2 abatement policy in one region may cause CO2 emissions to increase in non-abating regions because of the relocation of CO2-intensive firms and because of energy market effects. If, however, the CO2 mitigation policy induces energy-saving technological innovation in the home region and this innovation can freely spill-over to energy users abroad, carbon leakage may be offset by induced efficiency gains in foreign firms. In this paper we develop a simple mathematical model of carbon leakage and technological spillovers and perform numerical simulations with an adjusted CGE model to illustrate the potential importance of international technology spillovers. We show that carbon leakage can become negative at moderate levels of technology spillover.

Endogenous technical change, employment and distribution in the Goodwin model of the growth cycle

AbstractIn this paper, we introduce endogenous technological change through R&D expenditure on labor-augmenting innovation in the cyclical growth model by Goodwin (Goodwin, R. 1967. “A Growth Cycle.” In

INCREASING RETURNS TO SCALE, PRICE DISPERSION, AND THE DISTRIBUTION OF RETURNS TO INNOVATION

Models of endogenous growth have not been able to account for the variety of empirically observed distributional properties of the returns to innovation, in part, because of the limitations necessarily imposed on competition to cope with increasing returns to scale. Exponential growth, fat tails, Pareto–Levy distributed upper tails, and upper value outliers, are associated with increasing returns to scale and innovation. At the same time, properties such as bifurcated research investment strategies, bimodal returns to innovation, and Laplace distributed firm growth rates are products of competition. We build an agent-based model of endogenous technical change in which heterogeneous investments in patented knowledge and increasing returns to scale emerge these distributional properties within a competitive market. The combination of heterogeneous agents, costly information, and patents allow for a competitive landscape to persist amidst increasing returns. The ability of model to foster a coexistence of competition and increasing returns underlies the observed distributional properties.

Endogenous Capital Augmenting Technical Change and the Shape of Aggregate Production Function

In a neoclassical growth model with a constant elasticity of substitution production function, the conventional wisdom claims that capital augmenting technical change is labor biased and ceteris paribus increases the labor share when capital and labor are gross compliments. We construct an endogenous biased technical change model to challenge that interpretation. We show that capital augmenting technical change is capital biased and ceteris paribus decreases the labor share irrespective of the size of the elasticity of substitution. And we also provide a microfoundation for the induced aggregate production function to take the form of AK in the long-run.

Innovation benefits from nuclear phase-out: can they compensate the costs?

This paper investigates whether an inefficient allocation of abatement due to constraints on the use of currently available low carbon mitigation options can promote innovation in new technologies and have a positive impact on welfare. We focus on the case of a nuclear power phase-out and endogenous technical change in energy efficiency and alternative low carbon technologies. The research is inspired by the re-thinking about nuclear power deployment which took place in some countries, especially in Western Europe, after the Fukushima accident in March 2011. The analysis uses an Integrated Assessment Model, WITCH, which features multiple externalities related to greenhouse gas emissions and innovation market failures. Our results show that phasing out nuclear power stimulates R&D investments and deployment of technologies with large learning potential. The resulting technology benefits that would not otherwise occur due to intertemporal and international externalities almost completely offset the economic costs of foregoing nuclear power. The extent of technology benefits depends on the stringency of the climate policy and is distributed unevenly across countries.

Revisiting the Mechanism of Endogenous Technical Change for Climate Policy Analysis

Numerous climate policy modeling studies that feature endogenous technical change (TC) have emerged in the literature, but their endogenous specifications tend to diverge with little consensus on the underlying process. To reconcile disparate modeling methods, this paper revisits the mechanism of endogenous TC in climate policy analysis by developing a conceptual framework that captures three endogenous processes: R & D inducement, knowledge creation, and production technical change. I also provide methodological implications on how to incorporate this mechanism into a multi-sector computable general equilibrium (CGE) model, particularly the treatment on cross-sector knowledge spillovers and R & D crowding-out. Building on this generalized framework, climate policy modeling that seeks to incorporate endogenous TC can hopefully be supported in future studies.

The Poverty-Environment Trap in a Modified Romer Model with Dirtiness

The model presented in this paper describes an economy with endogenous technical change and polluting production techniques. The main question we want to address is whether the adoption of “dirty” production processes might lead to a sustainable unique steady state, or guarantee the emergence of multiple equilibria. The application of the original Bogdanov–Takens theorem allows us to characterize the regions of the parametric space where the model exhibits either a global indeterminate equilibrium or a poverty-environment trap.

Network Effects, Spillovers and Market Structure

This paper investigates the effect of spillovers in a model of endogenous technical change resulting from network effects as can be, for example, found in the market for hand‐held video consoles on the existence of a lower bound to market concentration.

Does Energy Constraint Facilitate the Japanese Technical Change?

This study challenges the traditional wisdom that soaring energy prices exert negative effects upon economic growth. For an industrialized country with very tight energy supply constraints, increasing energy costs may drive the firms to seek for technical change and innovation to compete internationally. Using the Japanese monthly data ranging from 1975 to 2010, this study tests for the assumption of endogenous cost-driven technical change. We identify a long-run equilibrium co-integrating relationship among the Japanese industrial production, energy prices, export volumes and export prices. Although energy prices are negatively associated with Japanese industrial production in static equilibrium, the results of Granger causality tests show that an increase in domestic energy costs has significantly positive effects on Japan’s industrial production as well as on export volumes and prices, in both short-run and long-run. We document that the seemingly paradox strongly suggests an endogenous technological change driven by energy costs in Japan.

Climate Change and Technical Progress: Impact of Informational Constraints

In this paper we analyse a growth model that includes environmental and economic variables as well as technological progress under different informational constraints on the behavior of economic agents. To simulate the informationally constrained economy, we make use of the non-linear model predictive control technique. We compare models with exogenous and endogenous technical change as well as directed and undirected endogenous technical change under different informational structures. We show that endogenous technical change yields lower environmental damages than exogenous technical change with fully informed agents. At the same time, welfare may rise or decline depending on the efficiency of the technology in use. In the case of directed technical change, a green growth scenario generates a smaller temperature increase that, however, goes along with less output and lower welfare. This holds both for informationally constrained and unconstrained behaviour of agents. We find that the effects of informational constraints, with respect to the climate system, increase with the degree of endogeneity of technology in the model.

Increasing Returns to Scale, Price Dispersion, and the Distribution of Returns to Innovation

Models of endogenous growth have not been able to account for the variety of empirically observed distributional properties of the returns to innovation, in part, because of the limitations necessarily imposed on competition to cope with increasing returns to scale. Exponential growth, fat tails, Pareto-Levy distributed upper tails, and upper value outliers, are associated with increasing returns to scale and innovation. At the same time, properties such as bifurcated research investment strategies, bimodal returns to innovation, and Laplace distributed firm growth rates are products of competition. We build an agent-based model of endogenous technical change in which heterogeneous investments in patented knowledge and increasing returns to scale emerge these distributional properties within a competitive market. The combination of heterogeneous agents, costly information, and patents allow for a competitive landscape to persist amidst increasing returns. The ability of model to foster a coexistence of competition and increasing returns underlies the observed distributional properties.

Option value in low-carbon technology policies

The political dilemma presented by the deployment of large-size low-carbon technologies (LCTs) is analysed using a simple dynamic model to investigate the relation between irreversible investments and learning-by-doing within a context of exogeneous uncertainty about the carbon price. It is shown that in some cases when information about the future carbon price is expected, the irreversibility effect holds and fewer LCT plants should be developed. In other cases, this result is reversed, and acquiring information can justify the early deployment of LCT. In particular, marginal reasoning is limited when learning-by-doing, and more generally endogenous technical change, is considered. When acquiring information is expected, the optimal policy can move from a corner optimum with no LCT deployment to an interior optimum with a strictly positive development.

Innovation Benefits from Nuclear Phase-Out: Can They Compensate the Costs?

This paper investigates whether an inefficient allocation of abatement, due to constraints on the use of currently available low carbon mitigation options, can promote innovation in new technologies and eventually generate welfare gains. We focus on the case of nuclear power phase out, when accounting for endogenous technical change in energy efficiency and in low carbon technologies. The analysis uses the Integrated Assessment Model WITCH, which features multiple externalities due to both climate and innovation market failures. Our results show that phasing out nuclear power stimulates additional R&D investments and deployment of infant technologies with large learning potential. The innovation benefits which this would generate and that would not otherwise be captured due to intertemporal and international externalities almost completely offset the economic costs of phasing out nuclear power. The technological change benefit depends on the stringency of the climate policy and is distributed unevenly across countries.

Economic and environmental effects under resource scarcity and substitution between renewable and non-renewable resources

We build a general equilibrium model with renewable (non-polluting) and non-renewable (polluting) resources to analyze the interaction and compatibility between economic growth and a cleaner environment. The study is in two phases: (i) resource extraction/production costs are constant; (ii) resource producers invest in knowledge to reduce extraction/production costs, endogenizing technical change. With constant costs, there is a permanent trade-off between economic growth and a cleaner environment. With endogenous technical change, it is possible to harmonize more output and less emissions by replacing non-renewable resources for renewable ones. We also conduct a sensitivity analysis to explore three specific policy actions. With constant costs, the best policy action is the imposition of a higher renewable resources standard, while with endogenous technical change, under certain conditions, all policy interventions may benefit both the economy and the environment.

Economic growth and polluting resources: Market equilibrium and optimal policies

This paper develops an endogenous growth model to study the decentralized equilibrium and the optimum conditions in an economy which uses polluting resources. The model includes two policy instruments, a subsidy to final consumption and an emissions tax. It also considers two forms of endogenous technical change, pollution-reducing knowledge and horizontal innovation. We show that, if the efficiency of knowledge to reduce emissions is sufficiently high, a higher output is compatible with lower emissions in both levels and growth rates. Additionally, if the two instruments are used together the economy may achieve a higher output and lower emissions since the subsidy may offset, at least partially, the negative tax effects.

Can technological innovation help China take on its climate responsibility? An intertemporal general equilibrium analysis

This paper examines the effectiveness of China’s indigenous R&D and technological innovation to curb its carbon emissions. The mechanism of endogenous technical change (TC) is incorporated an intertemporal computable general equilibrium (CGE) model. R&D investments and knowledge creations are modeled as the endogenous behaviors of private firms. The accumulated stocks of knowledge are applied in the production process to affect the rate and bias of TC. Simulation results show that: (1) while China’s indigenous R&D efforts play a significant role to curb carbon emissions, sole dependence on R&D may be far from sufficient to achieve pledged climate target, with complementary policies being required to reinforce existing climate actions; (2) innovation policies can strengthen R&D investment and cut emissions further, but the complementary effect is relatively minor; (3) carbon taxation can generate significant carbon-saving benefits and fulfill climate target, but this achievement is at the cost of economic losses. The induced technical improvement, however, can partially mitigate the deadweight loss incurred by carbon tax distortion.

Factor-Augmenting Technical Change: An Empirical Assessment

This paper estimates factor-specific technical change and input substitution using a structural approach. It contributes to the existing literature by introducing various technology drivers for factor productivities and by assessing the impact of endogenous technical change on the elasticity of substitution. The empirical results suggest that factor productivities are indeed endogenous. In addition, technology drivers are factor-specific. Whereas the R&D stock and machinery imports are important determinants of energy and capital productivity, the education stock is statistically related to labour productivity. The rate of energy-augmenting technical change is larger than that of either labour or capital. By contrast, the productivity of these two factors grows at similar rates. Estimates of the elasticity of substitution are within the range identified by previous literature. In addition, we show that endogenous technical change reduces substitution. Because the elasticity of substitution is lower than one, knowledge and human capital can ultimately have an energy-using effect. The estimated structure of endogenous technical change suggests that Integrated Assessment models focusing on energy-saving technical change might underestimate climate policy costs.

A review of uncertainties in technology experience curves

The use of log-linear experience curves (or learning curves) relating reductions in the unit cost of technologies to their cumulative production or installed capacity has become a common method of representing endogenous technical change in energy-economic models used for policy analysis. Yet, there are significant uncertainties in such formulations whose impact on key model results have been insufficiently examined or considered. This paper reviews the major types of uncertainty in log-linear experience curves and their effect on projected rates of cost reduction. Uncertainties are found not only in the learning rate parameter of a log-linear model, but also in the functional form that determines the shape of an experience curve. Evidence for alternative forms such as an S-shaped curve is reviewed along with case studies that demonstrate the uncertainties associated with cost increases during early commercialization of a technology—a phenomena that is widely recognized but rarely quantified or incorporated in learning models. Additional factors discussed include the effects of learning discontinuities, institutional forgetting, and the influence of social, economic and political factors. We then review other models of causality, which aim to improve modelers’ ability to explain and predict the influence of other underlying processes that contribute to technology cost reductions in addition to learning. Ignoring other types of underlying mechanisms can create a false sense of precision and overestimate the true contribution of learning. Currently, however, uncertainties in such multi-factor models remain large due to the difficulties of estimating key parameters (such as private-sector R&D investments) and extending models of a specific technology to a broader suite of technologies and cost projections. Pending the development and validation of more robust models of technological change, we suggest ways to significantly improve the characterization and reporting of current learning model uncertainties and their impacts on the results of energy-economic models to help reduce the potential for drawing inappropriate or erroneous policy conclusions.