Growth in this model is driven by technological change that arises from intentional investment decisions made by profit-maximizing agents. The distinguishing feature of the technology as an input is that it is neither a conventional good nor a public good; it is a nonrival, partially excludable good. Because of the nonconvexity introduced by a nonrival good, price-taking competition cannot be supported. Instead, the equilibrium is one with monopolistic competition. The main conclusions are that the stock of human capital determines the rate of growth, that too little human capital is devoted to research in equilibrium, that integration into world markets will increase growth rates, and that having a large population is not sufficient to generate growth.

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Endogenous Technological Change

Growth in this model is driven by technological change that arises from intentional investment decisions made by profit maximizing agents. The distinguishing feature of the technology as an input is that it is neither a conventional good nor a public good; it is a nonrival, partially excludable good. Because of the nonconvexity introduced by a nonrival good, price-taking competition cannot be supported, and instead, the equilibriumis one with monopolistic competition. The main conclusions are that the stock of human capital determines the rate of growth, that too little human capital is devoted to research in equilibrium, that integration into world markets will increase growth rates, and that having a large population is not sufficient to generate growth.

https://papers.ssrn.com/sol3/Delivery.cfm/nber_w3210.pdf?abstractid=226703&mirid=1

A model of endogenous growth is developed in which vertical innovations, generated by a competitive research sector, constitute the underlying source of growth. Equilibrium is determined by a forward-looking difference equation, according to which the amount of research in any period depends upon the expected amount of research next period. One source of this intertemporal relationship is creative destruction. That is, the prospect of more future research discourages current research by threatening to destroy the rents created by current research. The paper analyzes the positive and normative properties of stationary equilibria, in which research employment is constant and GNP follows a random walk with drift, although under some circumstances cyclical equilibria also exist. Both the average growth rate and the variance of the growth rate are increasing functions of the size of innovations, the size of the skilled labor force, and the productivity of research as measured by a parameter indicating the effect of research on the Poisson arrival rate of innovations; and decreasing functions of the rate of time preference of the representative individual. Under laissez faire the economy's growth rate may be more or less than optimal because, in addition to the appropriability and intertemporal spillover effects of other endogenous growth models, which tend to make growth slower than optimal, the model also has effects that work in the opposite direction. In particular, the fact that private research firms do not internalize the destruction of rents generated by their innovations introduces a business-stealing effect similar to that found in the partial-equilibrium patent race literature. When we endogenize the size of innovations we find that business stealing also makes innovations too small.

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A Model of Growth Through Creative Destruction

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

There is great uncertainty about future climate conditions and the appropriate policies for managing interactions between the climate and the economy. We develop a multidimensional computational model to examine how uncertainties and risks in the economic and climate systems affect the social cost of carbon (SCC)---that is, the present value of the marginal damage to economic output caused by carbon emissions. The SCC is substantially increased by economic and climate risks at both current and future times. Furthermore, the SCC is itself a stochastic process with significant variation; for example, the basic elements of risk incorporated into our model cause the SCC in 2100 to be, with significant probability, ten times what it would be without those risks. We have only imprecise information about what parameter values are best for approximating reality. To deal with this parametric uncertainty we perform extensive uncertainty quantification and show that these findings are robust for a wide range of alternative specifications. More generally, this work shows that large-scale computing can enable economists to examine substantially more complex and realistic models for the purposes of policy analysis.

The Social Cost of Carbon with Economic and Climate Risks

http://www.robertkollmann.com/DEN_HAAN_JUDD_JUILLARD_INTRODUCTION_JEDC_2010.pdf

Computational suite of models with heterogeneous agents: Incomplete markets and aggregate uncertainty

Approximation, perturbation, and projection methods in economic analysis

Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.

https://www.pnas.org/content/pnas/112/15/4606.full.pdf

Environmental tipping points significantly affect the cost-benefit assessment of climate policies.

Discrete-time stochastic games with a flnite number of states have been widely applied to study the strategic interactions among forward-looking players in dynamic environments. However, these games sufier from a \curse of dimensionality" since the cost of computing players’ expectations over all possible future states increases exponentially in the number of state variables. We explore the alternative of continuous-time stochastic games with a flnite number of states, and show that continuous time has substantial computational and conceptual advantages. Most important, continuous time avoids the curse of dimensionality, thereby speeding up the computations by orders of magnitude in games with more than a few state variables. Overall, the continuous-time approach opens the way to analyze more complex and realistic stochastic games than currently feasible.

/pdf/avoiding-the-curse-of-dimensionality-in-dynamic-stochastic-39xh37gv3q.pdf

Kenneth L. Judd

Papers

The Social Cost of Carbon with Economic and Climate Risks

Computational suite of models with heterogeneous agents: Incomplete markets and aggregate uncertainty

Approximation, perturbation, and projection methods in economic analysis

Environmental tipping points significantly affect the cost-benefit assessment of climate policies.

Avoiding the curse of dimensionality in dynamic stochastic games