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Effects of R&D Subsidies on Regional Economic Dynamics: Evidence from Chinese Provinces
Abstract
We investigate the impact of research and development (R&D) subsidies on R&D inputs of large- and medium-sized firms and on additional innovation and economic activities in Chinese provinces. A panel vector autoregressive (VAR) model and corresponding impulse response function (IRF) analysis allow us to differentiate between direct and indirect effects, which add up to total effects. We find that an increase of R&D subsidies significantly decreases private R&D investments, although there is a significant positive effect on the R&D personnel employed in firms. We interpret these findings as a partial crowding-out effect because public funds substitute some private funds while total R&D inputs still increase. Complementarily, we find a positive secondary effect on the provincial patent activity, our measure of technological progress. Interestingly, we also find potentially unintended effects of R&D subsidies on increases in the investment rate in physical capital and residential buildings. Although R&D subsidies fail to incentivise private R&D expenditures, firms increase total R&D inputs, and provincial economies benefit from secondary effects on technological progress and capital deepening.
City-level accounting of industrial green productivity (IGP) is necessary to identify the different circumstances of industrial green transformation and development across Chinese cities. However, the lack of energy consumption data in the urban industrial sector leads to the assessment of China’s IGP at the macro provincial level, which is not conducive to further formulating systematic measures to improve IGP. Hence, based on the multi-source nighttime light (NTL) data fitted and corrected by DSMP/OLS and NPP/VIIRS images, this study simulates the total energy consumption of urban industrial sector and establishes an IGP analysis database combined with socio-economic data. Subsequently, the spatiotemporal pattern and drivers of IGP are systematically investigated by means of the Dagum Gini coefficient, spatial autocorrelation model, Markov transition probability matrix, and spatial econometric model. Four important findings arise from the analyses. Stylized facts show that an overall increase in IGP is accompanied by the exacerbation in spatial inequality, the year 2006 is a turning point from frequent fluctuations to steady growth. Specifically, interregional disparities have gradually become the main source of overall disparities in IGP across eight comprehensive economic zones, hypervariable density is the main source of overall disparities across three major urban agglomerations. Spatially, Global Moran’s I of IGP uninterruptedly increases from 0.043 in 2008 to 0.155 in 2017, showing a positive spatial correlation of high-high agglomeration and low-low agglomeration. Additionally, IGP has a strong spatial locking effect with the unchanged probability of 78.81%, 72.18%, 75.94%, 83.67%, and there is the coexistence of win–win and beggar-thy-neighbor phenomenon to a large extent. Results further reveal that IGP has a positively spatial spillover effect, economic development level, human capital, industrial agglomeration, and environmental regulations all work for driving IGP growth in local and neighboring areas. Based on the findings, policy recommendations for the improvement of IGP are provided.
This article investigates the impact of academia-industry collaboration (AIC) on regional innovation convergence in China from the perspective of innovation ecosystem. Using the methods of σ-convergence and β-convergence, we explore the effect of AIC on innovation convergence among provinces over time, taking into account of the flow of talents, regional economic development level and degree of openness. AIC is classified into two types: university-industry cooperation (UIC) and industry-research-institute cooperation (IRC). We find that while innovation performance is divergent across regions, AIC can significantly weaken the divergence, and the effect of UIC on the convergence is especially obvious. After dividing the country into eastern, central and western subsamples, we find that AIC significantly promotes regional innovation convergence in the central area. Both UIC and IRC significantly inhibit innovation divergence in the central sample. Furthermore, UIC also shows the same effect in the western sample. Our research indicates that the current innovation ecosystem has not yet achieved the desired results and improving its performance requires policies to adapt to local conditions.
The implementation of innovation-driven strategy is of great significance. Analysis of the driving factors of innovation performance from quantitative and systematic perspectives is needed for policy making. By drawing upon the LMDI model, this study identifies the driving factors and their corresponding contributions in the innovation performance of 30 Chinese provincial-level regions during the period 2000–2012. The innovation performance is decomposed into the regional economic structure effect, R&D intensity effect, innovation efficiency effect, and economic development effect according to the driving mechanism. The results indicate that the third effect in this list, innovation efficiency, contributes the most to innovation performance at 54.28%, followed by the regional R&D intensity at 27.49%, and China’s economic development at 19.92%. The effect of the regional economic structure is negative, at −1.69%. This study further analyzes four major economic areas of China and identifies the channels through which each area conducts their innovation activities. The empirical findings provide information for policy measures to implement innovation-driven strategies.
Whether the People's Republic of China's (PRC) economic slowdown since the 2008 financial crisis is a cyclical downturn or a long-run trend has important policy implications. As productivity is the determinant factor for long-term economic growth and the PRC watches soaring labor cost while no serious unemployment recently, this article tries to understand its slowdown from the supply side. Based on provincial panel data, it first identifies the determinants of productivity growth and then uses counterfactual analysis to simulate effects of the PRC's policy-induced investment boom on its economic growth. It finds that economic openness enhances productivity, whereas economies at higher stages of development on average have lower productivity growth. Second, productivity of economies accumulating more stock of inventory grows more slowly, while the opposite is observed for those with higher labor involvement rates. Third, government size and investment rate both have significantly negative effects on productivity growth. Finally, the diminishing late-mover advantage and the growth in investment rate are both major contributors to the current decline in the PRC's productivity growth. The current economic slowdown does not seem to be a cyclical downturn. Indeed, further reforms are needed to stabilize the PRC's growth.
This study investigates the effects of government R&D programs on firm innovation outputs, which are measured by the number of patents, sales from new products, and exports. Particularly, we examine the effects of Innovation Fund for Small and Medium Technology-based Firms (Innofund), which is one of the largest government R&D programs that support R&D activities of small and medium-sized enterprises in China. Using a panel dataset on Chinese manufacturing firms from 1998 to 2007, we find that Innofund-backed firms generate significantly higher technological and commercialized innovation outputs compared with their non-Innofund-backed counterparts and the same firms before winning the grant. Moreover, the changes in the governance of Innofund in 2005 from a centralized to a decentralized one because of policy amendments have significant effects on the effectiveness of the program. Specifically, the magnified effects of Innofund on technological innovation outputs become significantly stronger after the governance of Innofund becomes more decentralized. Identification problems are addressed by utilizing both propensity score matching and two-stage estimation approaches.
There is growing anxiety among Chinese political and scientific leaders that, despite more money, better-trained talent, and sophisticated equipment, the domestic innovation system is still underperforming ( 1 ). Chinese scientists have yet to produce breakthroughs worth a Nobel Prize. Research and business sectors have been disconnected for decades, with few research results turned into innovative technology and products. With few exceptions, Chinese enterprises depend on foreign sources for core technologies ( 2 ). We discuss interwoven roots of these problems at macro, meso, and micro levels of governance of the science and technology (S&T) system and the need for political will if they are to be overcome.
This study presents an approach to identify nancing constraints for innovation. Firms were oered a hypothetical payment and were asked to choose between alternatives of use. We attribute constraints for innovation not only to lacking nancing, but also to rms' innovation capacity. Econometric results show that nancial constraints do not depend on the availability of internal funds per se, but are driven by innovation capacity. We nd rms with high innovation capacity but low nancial resources to be most likely face constraints. Yet, we also observe constraints for nancially sound rms that may have to put ideas on the shelf.
We introduce a new hybrid approach to joint estimation of Value at Risk (VaR) and Expected Shortfall (ES) for high quantiles of return distributions. We investigate the relative performance of VaR and ES models using daily returns for sixteen stock market indices (eight from developed and eight from emerging markets) prior to and during the 2008 financial crisis. In addition to widely used VaR and ES models, we also study the behavior of conditional and unconditional extreme value (EV) models to generate 99 percent confidence level estimates as well as developing a new loss function that relates tail losses to ES forecasts. Backtesting results show that only our proposed new hybrid and Extreme Value (EV)-based VaR models provide adequate protection in both developed and emerging markets, but that the hybrid approach does this at a significantly lower cost in capital reserves. In ES estimation the hybrid model yields the smallest error statistics surpassing even the EV models, especially in the developed markets.
The aim of this paper is to analyse the effects of regional investment incentives - a main component of regional policy in West Germany - on regional factor demand (investment and labor), growth and convergence of per capita income for the period 1978 to 1989. Demand for investment and labor arise from a model of cost minimization at given output with a putty-clay production function. The production function allows for regional technical efficiency. To model the output effect on factor demand an auxiliary output function is specified. In estimating the functions attention is given to the short-run dynamics and the long-run behaviour of factor demand by error-correction models. The empirical long-run relationships are then used to simulate the effects of regional investment incentives. In contrast to most studies for other countries the empirical results provide evidence that regional policy in Germany induces not only additional investment but also creates positive employment effects. However, the effects of regional investment incentives on growth and convergence of labor productivity are negligible.
This paper analyzes the method of social experiments. The assumptions that justify the experimental method are exposited. Parameters of interest in evaluating social programs are discussed. The authors show how experiments sometimes serve as instrumental variables to identify program impacts. The most favorable case for experiments ignores variability across persons in response to treatments received and assumes that mean impacts of a program are the main object of interest in conducting an evaluation. Experiments do not identify the distribution of program gains unless additional assumptions are maintained. Evidence on the validity of the assumptions used to justify social experiments is presented. Copyright 1995 by American Economic Association.
We study a Chinese policy that awards substantial tax cuts to firms with R&D investment over a threshold or “notch.” Quasi-experimental variation and administrative tax data show a significant increase in reported R&D that is partly driven by firms relabeling expenses as R&D. Structural estimates show relabeling accounts for 24.2 percent of reported R&D and that doubling R&D would increase productivity by 9 percent. Policy simulations show that firm selection and relabeling determine the cost-effectiveness of stimulating R&D, that notch-based policies are more effective than tax credits when relabeling is prevalent, and that modest spillovers justify the program from a welfare perspective. (JEL D22, D24, H25, O14, O32, P31, P35)
Purpose
This paper aims to investigate whether a complementary effect exists between government R&D subsidies (GRSs) and intellectual property rights (IPR) protection on innovation performance in the pharmaceutical manufacturing industry in China. This paper also attempts to understand whether this complementary effect is significantly different across China’s eastern, central and western regions.
Design/methodology/approach
The study sample comprised 28 provinces involved in the pharmaceutical manufacturing industry in China from 2003 to 2014. Ordinary least squares was used to test the complementary effects of GRSs and IPR protection on innovation performance. The seemingly unrelated estimation test was also applied to ascertain whether differences existed between the eastern and western regions.
Findings
A complementary effect between GRSs and IPR protection in terms of improving the innovation of pharmaceutical manufacturers was found to exist only in eastern and western regions. There was no significant difference in the complementary effect between GRSs and IPR protection in terms of improving innovation among the three regions. Without considering the interaction effect of GRSs and IPR protection, the GRSs were negatively associated with innovation in the eastern region, but positively related to the innovation in central region.
Originality/value
This study contributes to the literature on government policies and innovation by incorporating the interaction effect of GRSs and IPR protection on innovation in the context of a high-tech industry (pharmaceutical manufacturing) in an emerging economy (China). It also explores the internal differences in the influence of this complementary effect on innovation in an emerging economy, enriching the institution-based view.
We examine whether receiving a government R&D grant stimulates or crowds out a firm's own R&D spending in Chinese manufacturing industries. Using a database that spans the population of large and medium size privately owned Chinese manufacturing firms for the period from 2007 to 2011, a matching estimator and a matching and difference in‐differences estimator, we find a large firm R&D promoting effect of government R&D: receiving a government R&D grant led to a 4 to 9‐million‐yuan increase in a firm's own R&D expenditures. This is a significant effect since the average R&D expenditures ranged from 5 to 9 million yuan in the year before receiving the grant. To understand the mechanisms behind this effect, we compare the before‐ and after‐treatment performance and behaviour of the treated and the control firms. We find that the government R&D receiving firms became more profitable following their receipt of the grant. We also find that receiving a government R&D grant increases the likelihood of a firm continuing its R&D performance after receiving the initial grant.
en This paper investigates the mutual impact channels of Germany's major regional policy instrument (GRW) on regional economic development. Different from earlier studies which have predominately focused on a partial assessment of output effects, we explicitly endogenize the factor inputs of the underlying production function. This allows us to comprehensively assess the role of the GRW in driving per capita output, employment, human and physical capital intensities as well as the region's technological growth. The results from a spatial panel vector autoregressive model show that GRW funding has significant positive effects on regional output, the employment rate and human capital intensity.
Resumen
es Este artículo investiga los canales de impacto mutuo del principal instrumento de política regional (GRW, por sus siglas en alemán) de Alemania sobre el desarrollo económico regional. A diferencia de estudios anteriores, que se han centrado predominantemente en una evaluación parcial de los efectos de la producción, este estudio interioriza explícitamente los insumos de los factores de la función de producción subyacente. Esto permite evaluar de manera integral el papel del GRW en el impulso de la producción per cápita, el empleo, las intensidades de capital humano y físico, así como el crecimiento tecnológico de la región. Los resultados de un modelo de panel espacial vectorial autorregresivo muestran que la financiación del GRW tiene efectos positivos significativos en la producción regional, la tasa de empleo y la intensidad del capital humano.
抄録
ja 本稿では、ドイツの主な地域の政策手段 (GRW)の、地域の経済発展に対する相互作用のチャネルを検討する。アウトプット効果の部分的な評価に特に重きを置いていた過去の研究と異なり、本研究では、根底にある生産機能の要素投入量を明確に内生化する。これによって、GRWの、一人当たり生産額、雇用、人的資本および物理的資本の集約度の他に、地域の技術的成長の促進における役割を包括的に評価することができる。空間的パネルベクトル自己回帰モデルによる分析の結果から、GRWによる資金調達は、地域の生産額、雇用率、人的資本の集約度に対して有意な正の効果があることが示される。
After more than three decades of high growth based on its low-wage advantage and relatively favorable demographics--in combination with market-oriented reforms and openness to the world economy--China is at a crossroads with a much higher wage and a shrinking workforce. Future growth will depend, by necessity, more on the generation of increased productivity, and domestic innovation will play an important part in this. In this paper, we assess the likelihood that China can make the necessary transition. Using data on expenditure on research and development, and patent applications, receipts, and citations, we show that the Chinese economy has become increasingly innovative. We will argue that rising wages and expanding markets are among the important drivers of China's growth in innovation. On the other hand, we find evidence of resource misallocation in the innovation area: while state-owned firms receive more subsidies, private firms exhibit more innovation results. Innovation can presumably progress even faster if resource misallocation can be tackled.
In this study we investigate the allocation of China's R&D subsidies and their effectiveness in stimulating business R&D investments for the population of Chinese listed firms between 2001 and 2006. With respect to subsidy allocation, we find that firm selection is mainly determined by prior grants, high quality inventions, and minority state-ownership. Market-oriented provincial governments distribute grants less frequently, and firms located in developed provinces receive grants more often. Considering effectiveness, R&D subsidies instantaneously crowd-out business R&D investment but are neutral in later periods. In 2006, one public RMB reduces business R&D investments by half an RMB. However, crowding-out is not prevalent for repeated recipients of R&D subsidies, high-tech firms, and minority state-owned firms.
The impact of housing price appreciation on firm innovation may be negative. Housing price appreciation generates real estate investment opportunities with high returns, making manufacturing firms more likely to diversify into the real estate industry. With limited resources, once investing in real estate development, these firms will invest less in innovation. By examining manufacturing firms in China for the period 1999-2007, we provide evidence by finding that housing price appreciation negatively influenced manufacturing firms’ innovation propensities. Additionally, we further explore the underlying mechanism by examining the likelihood of listed firms’ diversification into the real estate industry, and how the diversification influenced their patenting. Consistent with the investment opportunity hypothesis, we find that (1) housing price appreciation stimulated firms to enter the real estate industry, and a firm's invention patenting was negatively influenced subsequent to its real estate diversification; (2) the negative effect was more pronounced where housing price growth rates were higher.
Using HWA-MWECR-CVD system μc-Si; H thin films were prepared. The influences of hydrogen dilution ratio, reaction pressure and microwave power on the amorphous to microcrystalline phase transition, deposition rate and photo-electronic properties of thin films were studied. The experimental results showed that under the conditions of 94% hydrogen dilution ratio, 1.5 Pa reaction pressure and 500 W microwave power, high-quality μc-Si:H thin films were obtained, such as high photosensitivity of 2.86 * 104, high deposition rate of about 1 nm/s and low light-induced degradation rate of 8.9%, etc.
Using a merged dataset of Chinese patent data and industrial survey data, we make a bibliometric analysis of patenting activities of Chinese large and medium-sized enterprises under local patent subsidy programs and test whether patent statistics are a good indicator of innovation in China. Our empirical results show that patent count is correlated with R&D input and financial output, which suggests that patent statistics are meaningful indicators. However, patent subsidy programs increase patent counts more than 30%. We emphasize the necessity of adjustments and provide a novel method of using the number of nouns in claims to quantify the claim scope, thereby overcoming the shortcomings of Chinese patent data that have no citations or lack well-documented patent claim information. We extend prior studies on patent subsidy programs by providing a detailed clarification of policy designs and their impacts and by evaluating policy impacts on both the quantity and quality of patent applications.
I. Introduction, 65. — II. A model of long-run growth, 66. — III. Possible growth patterns, 68. — IV. Examples, 73. — V. Behavior
of interest and wage rates, 78. — VI. Extensions, 85. — VII. Qualifications, 91.
Much controversy about causality and related concepts has arisen in the philosophical literature, and the haze surrounding the discussion has spread to other fields, among them econometrics. This brief outline stresses certain general principles and ideas that are relevant for actual research activity in the natural and social sciences. The main points are: (1) The concept of causality is indispensable and fundamental to all science; (2) The controversial issues are not latent in the concept of causality itself, but in certain questionable hypotheses, so-called "laws of causality," such as the universal scope of causality, the certainty (irrevocability) of a cause-effect relationship, the connection of causality with theories of induction, the principles of determinism and freedom of the will, etc; (3) A definition of causality which seems to be adequate from both common-sense and scientific points of view is suggested with reference to the well-known situation of the controlled experiment; (4) Some general remarks on statistical methods from the viewpoint of the dual distinction between descriptive and explanatory analysis and between experimental and nonexperimental observations are made; (5-6) Some comments are offered on causal relations as a tool in econometrics, with special regard to the rationale of different types of economic models.
This article contributes to the recent literature in spatial econometrics that focuses on space–time data modeling implementing a multilocation time-series statistical framework to analyze a regional system. Drawing on the global vector autoregression approach introduced in Pesaran, Schuermann, and Weiner, a multiregional spatial vector autoregressive (MultiREG-SpVAR) model is formulated and then applied to study the spatiotemporal transmission of macroeconomic shocks across the regions in Spain. The empirical application analyzes the extent to which a region’s economic output growth is influenced by the growth of its neighbors (push-in or inward growth effect), and also investigates the relevance of spillovers derived from temporary region specific output growth shocks (push-out or outward growth effect). Our results identify some regions that perform as ‘‘growth generators’’ within the Spanish regional system since growth shocks from these regions spillover to a large number of regions of the country, playing a key role in the transmission of regional business cycles. The policy implications of our results suggest that national and/or regional governments should stimulate economic activity in these leading regions in order to enhance the economic recovery process of the whole Spanish economy.
This survey examines the empirical literature on the relationship between public R&D
subsidies and private R&D investment over the past five decades. The survey reveals a considerable heterogeneity of empirical results that cannot be explained fully by methodological issues. We aim to provide further explanations of the possible causes of that heterogeneity. In particular, we emphasise a set of issues that, in our view, are critical to understanding the potential effect of public R&D subsidies on private R&D spending. Special attention is paid to the dynamic aspects and composition of firm R&D, the constraints faced by the firm (such as financial constraints), and the amount and source of public subsidies. None of these issues have been investigated in depth. We formulate a set of research assumptions to guide future empirical research in this field.
This paper assesses both interregional and intraregional innovation inequality in China from 1995 to 2006. It is revealed that the east–central–west inequality has increased over time, whereas the inter‐provincial inequality showed a V‐pattern until 2003; Both inequality measures oscillated from 2004 to 2006. Using a decomposition framework recently developed by one of the authors, we determined that the major factors driving innovation inequality are population, economic development level, R&D, location and openness. The aggravated innovation inequality reflects the growth of China's innovation centers in the eastern region and their admission into the global innovation networks. The fact that R&D is a major factor driving the inequality suggests that, considered in the present study, the efficiency of R&D investment improved in certian regions during the period (1995–2006). Finally, geographic location and openness affect innovation inequality primarily through the coupled evolution of innovation capability and economic development, resulting in first‐mover advantages to provinces of the eastern region.
Drawing upon regional innovation system literature, this paper estimates a stochastic frontier model to explain the increasing disparity in innovation performance between Chinese regions. The estimated results show that government support, the constitution of the R&D performers, and the regional industry-specific innovation environment are significant determinants of innovation efficiency. Due to the large difference in the firms’ innovation performance across the regions, when regional innovation modes are transformed from university and research institute dominant to firm dominant, the overall innovation efficiency between regions becomes more and more disparate, which actually underlies the widening gap in regional innovation performance.
Is public R&D spending complementary and thus “additional” to private R&D spending, or does it substitute for and tend to “crowd out” private R&D? Conflicting answers are given to this question. We survey the body of available econometric evidence accumulated over the past 35 years. A framework for analysis of the problem is developed to help organize and summarize the findings of econometric studies based on time series and cross-section data from various levels of aggregation (laboratory, firm, industry, country). The findings overall are ambivalent and the existing literature as a whole is subject to the criticism that the nature of the “experiment(s)” that the investigators envisage is not adequately specified. We conclude by offering suggestions for improving future empirical research on this issue.
The within or least-squares dummy variable estimator is inconsistent for homogeneous dynamic panel models with fixed time dimension T. We present a bias correction for this estimator based on an iterative bootstrap procedure. Monte Carlo simulations show that, for panels with small to moderate T, this procedure provides a good alternative for existing dynamic panel data estimators.
Despite a history of regional economic models being patterned after their national counterparts, modern macroeconomic methodology has yet to be fully embraced by regional scientists. In this paper, I argue that modern macroeconomic methodology has much to offer the field of regional economic modeling. For one, the empirical strategies used in implementing dynamic stochastic general equilibrium models provide insights into how regional computable general equilibrium models could be better parameterized and empirically verified. In addition, the structural macroeconomic approach more generally could be used to construct structural regional policy analysis models for use as alternatives to traditional regional models. Copyright (c) 2010, Wiley Periodicals, Inc.
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 not a conventional good or a public good; it is a nonrival, partially excludable good. Because of the noconvexity 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 a large population is not sufficient to generate growth. Copyright 1990 by University of Chicago Press.
In a world with two similar, developed economies, economic integration can cause a permanent increase in the worldwide rate
of growth. Starting from a position of isolation, closer integration can be achieved by increasing trade in goods or by increasing
flows of ideas. We consider two models with different specifications of the research and development sector that is the source
of growth. Either form of integration can increase the long-run rate of growth if it encourages the worldwide exploitation
of increasing returns to scale in the research and development sector.
It is found that patents in China are highly clustered in two groups of provinces: one is the economically fast growing coastal provinces; and the other is inland provinces with large bases of populations, while the degree of spatial concentration of patents is declining over time. It is also revealed that export, together with 'technical infrastructure' including producer services and development of technology transfer market explains most of the provincial variation of patents. Furthermore, foreign ventures do not seem to be an important player in China's innovation system, while both state-owned and collective-owned industries contribute significantly to creations of new products in China. Finally, some commonly cited significant factors for innovations in western literature such as research and development (R and D) and agglomeration do not seem to explain the spatial distribution of patents in China. It is argued that such discrepancies between western 'common sense' and Chinese experience are largely attributed to China's inefficient innovation system, which has not been able to develop its potentiality.
This comprehensive introduction to economic growth presents the main facts and puzzles about growth, proposes simple methods and models needed to explain these facts, acquaints the reader with the most recent theoretical and empirical developments, and provides tools with which to analyze policy design. The treatment of growth theory is fully accessible to students with a background no more advanced than elementary calculus and probability theory; the reader need not master all the subtleties of dynamic programming and stochastic processes to learn what is essential about such issues as cross-country convergence, the effects of financial development on growth, and the consequences of globalization. The book, which grew out of courses taught by the authors at Harvard and Brown universities, can be used both by advanced undergraduate and graduate students, and as a reference for professional economists in government or international financial organizations. The Economics of Growth first presents the main growth paradigms: the neoclassical model, the AK model, Romer's product variety model, and the Schumpeterian model. The text then builds on the main paradigms to shed light on the dynamic process of growth and development, discussing such topics as club convergence, directed technical change, the transition from Malthusian stagnation to sustained growth, general purpose technologies, and the recent debate over institutions versus human capital as the primary factor in cross-country income differences. Finally, the book focuses on growth policies—analyzing the effects of liberalizing market competition and entry, education policy, trade liberalization, environmental and resource constraints, and stabilization policy—and the methodology of growth policy design. All chapters include literature reviews and problem sets. An appendix covers basic concepts of econometrics.
Conventional wisdom holds that the social rate of return to R&D significantly exceeds the private rate of return and, therefore, R&D should be subsidized. In the U.S., the government has directly funded a large fraction of total R&D spending. This paper shows that there is a serious problem with such government efforts to increase inventive activity. The majority of R&D spending is actually just salary payments for R&D workers. Their labor supply, however, is quite inelastic so when the government funds R&D, a significant fraction of the increased spending goes directly into higher wages. Using CPS data on wages of scientific personnel, this paper shows that government R&D spending raises wages significantly, particularly for scientists related to defense such as physicists and aeronautical engineers. Because of the higher wages, conventional estimates of the effectiveness of R&D policy may be 30 to 50% too high. The results also imply that by altering the wages of scientists and engineers even for firms not receiving federal support, government funding directly crowds out private inventive activity.
Exxon Mobil and ConocoPhillips stock price has been predicted using the difference between core and headline CPI in the United States. Linear trends in the CPI difference allow accurate prediction of the prices at a five to ten-year horizon.
Productivity in Chinese industry: 1998-2013
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