Indeterminacy and multiple steady states with sector-specific externalities

This paper studies a two-sector model with aggregate and sector-specific external effects in production and inelastic labor supply. We first characterize the existence, uniqueness and multiplicity of the steady states as well as their welfare properties. We particularly focus on the CES production functions and show that the steady state is generically either unique or there are exactly two. A simple geometrical methodology enables us to characterize the local dynamics of the steady state. We show that in order to get indeterminacy, the presence of both aggregate and sector-specific external effects is needed, along with low capital–labor elasticities of substitution and high, but bounded from above, elasticities in intertemporal consumption. We perform a sensitivity analysis and show that indeterminacy emerges for parameter values in line with those used in calibrations of standard RBC models, that is for unitary elasticities of input substitution and of intertemporal substitution in consumption.     

Generalized Lotka-Volterra equations and the mechanism of technological substitution

This paper demonstrates that if technological substitution is viewed as the result of competition between old and new technology in which new technology wins, and if generalized Lotka-Volterra equations are taken to describe this competition, then various models of technological substitution can be obtained as very special cases. It is argued that this could lead to a better understanding of the substitution process itself.     

The difference,system and ‘Double‐D’ GMM panel estimators in the presence of structural breaks

The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto‐regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.     

A new estimator for trade costs and its small sample properties

This paper discusses the estimation of parameters of a traditional transportation model, as it is typically present in so-called Takayama–Judge type spatial price equilibrium models. In contrast to previously used estimation methods, observations of regional prices as well as of trade costs are used in a direct estimation of the first order conditions. The proposed method uses bi-level programming techniques to minimize a weighted least squares criterion under the restriction that the estimated parameters satisfy the Kuhn–Tucker conditions for an optimal solution of the transport model. A penalty function and a smooth reformulation are used to iteratively approximate the complementary slackness conditions. Monte-Carlo simulations are used to trace out some properties of the estimator and compare it with a traditional calibration method. The analysis shows that the proposed technique estimates prices as well as trade costs more precisely than the traditional calibration method. It is suggested to apply the same method to a range of linear and quadratic models.     

Long-run relationships between labor and capital: Indirect evidence on the elasticity of substitution

This paper proposes an indirect method for making empirical inference on the elasticity of substitution between capital and labor. The idea is that estimates of the elasticity may be retrievable from theory derived behavioral equations, by conducting comparative statics with respect to this parameter. This approach is readily applicable to more realistic models than those which are commonly used to derive estimates of the substitution elasticity. It is demonstrated that the conventional approach does not yield sensible estimates on quarterly Finnish manufacturing data. By applying the indirect method, a long-run empirical relationship is found that is consistent with an elasticity of substitution below one.     

Oil shocks and the dynamics of substitution adjustments of industrial fuels in the US

This paper investigates substitution among such alternate fuels as coal, natural gas, and electricity during the actual oil price increases of 1970s. These substitution adjustments are assumed to be dynamic and modelled by a partial adjustment structure. This dynamic structure is incorporated into a translog cost technology. Short- and long-run price elasticities are estimated by identifying inter- and intra-industry variations. The models are estimated with a sample of 88 pooled observations, including distillate and residual oils purchased by eleven 2-digit manufacturing groups (1974-81). Models are estimates are strictly negative. These own price elasticities range from (long-to short-run) –2.93 to –2.55 for distillate oil, –0.698 to – 1.53 for residual oil, –0.533 to 0.011 for coal, –0.235 to –0.213 for natural gas, to –0.888 to –0.845 for electricity. Estimastes of both short-run and long-run cross-price elasticities suggest that coal and electric energy are the prominent substitutes for fuel oils. While the relationship between the latter and natural gas remains largely complementary.     

中国的产业结构与就业问题

我国近年来就业矛盾十分突出,通过对历史数据和国际数据的比较研究,发现就业矛盾的原因在于劳动就业结构滞后与产业结构的变化,产生了结构性偏差,并且偏差的收敛速度慢于国际经验.分别从三次产业看,偏差产生的原因是农业劳动力转移缓慢,工业生产中普遍采用了劳动节约型技术,发生资本替代劳动,以及第三产业增长缓慢和结构失调.基于结构的观点,我们提出了相应的政策建议.     

Reassessing the empirical validity of the human-capital augmented neoclassical growth model

We reassess Mankiw, Romer and Weil's [mrw] version of the Solow model using, as did mrw, cross-sectional data to estimate the steady-state equation governing income per capita levels. The model fails in two critical areas. First, plausible factor shares obtained by mrw are not robust to the substitution of two measures of human capital that are more precise than the secondary school enrollment rates used by mrw. Second, the null hypothesis of an exogenous and identical level of technology in all countries is rejected. We also explain why the Solow model performed well despite the above shortcomings.     

A model for forecasting the substitution of one technology for another

Most technological changes can be described as a substitution of one material, process or product for another. Each such substitution, if successful, normally tends to follow an S-shaped (or “logistic”) curve: that is, it starts slowly as initial problems and resistances have to be overcome; then it proceeds more rapidly as the competition between the new and the old technology grows keener and the new technology gains an advantage; and finally, as the market for the new technology approaches saturation, the pace of substitution slows down. Sometimes, when the process is completed, the old technology continues to retain some specialized portion of the total market (i.e., a sub-market) for which it is particularly well adapted. In forecasting the course and speed of the substitution process especially when it has already begun and partially taken place, the simplest approach is to project a function having the appropriate S-shaped curve, using historical data to determine the free parameters of the function. While useful, especially where data are not available for a more sophisticated study, the simple curve-fitting techniques fail to take into account several important factors that affect economic and management decisions on the part of producers and intermediate users (as well as “final” consumers) and thereby influence the course which the substitution process is likely to take. To overcome this limitation, a simulation model has been developed at IR&T which allows some of these factors to be evaluated and incorporated explicitly and quantitatively. The model is described and its application is illustrated in the case of the substitution of plastic for glass in bottles. It is most applicable where the competing technologies are rather precisely defined, where a good deal of current technical and economic data are available, and where an in-depth analysis is desired. Because this particular forecast was made before the sudden precipitous increase in petroleum prices, which upsets the price relationships assumed in the forecast, there is discussion of the vulnerability of forecasts to political and other contra-economic developments.     

Determinants for forecasting technological substitution

This paper investigates the factors determining the rate of technological substitution and evaluates the prospects for forecasting models based on market-share data only. Studies on underlying causes for the substitution of one technology or product by another reveal the frequent presence of a number of factors. These factors are first discussed in general terms so as to establish their causal relationships with the rate of substitution. On the basis of the identified cause-effect relationships, a composite model is formulated that incorporates the impact of individual factors in a combination of additive and multiplicative interactions. The relative importance and sensitivity of different factors in describing the behavior of the substitution process is then studied through a system-dynamics application of the model. Finally, using three specific cases, a comparison is given between the forecasts made by the comprehensive model, incorporating factors that are known to have significant impact on the rate of substitution, with that of a generalized model for forecasting technological substitution.     

A medium-N approach to macroeconomic forecasting

This paper considers methods for forecasting macroeconomic time series in a framework where the number of predictors, N, is too large to apply traditional regression models but not sufficiently large to resort to statistical inference based on double asymptotics. Our interest is motivated by a body of empirical research suggesting that popular data-rich prediction methods perform best when N ranges from 20 to 40. In order to accomplish our goal, we resort to partial least squares and principal component regression to consistently estimate a stable dynamic regression model with many predictors as only the number of observations, T, diverges. We show both by simulations and empirical applications that the considered methods, especially partial least squares, compare well to models that are widely used in macroeconomic forecasting.     

Dynamics of social factors in technological substitutions

Diffusion models of technological innovations are often based on an epidemic structure which has a good fit to historical data but whose communication assumptions lack explanatory power. They assume a simplified decision process, uniform decision criteria across adopters categories, and a fully interconnected social structure. The objective of this paper is to show that the dynamics of social factors during technological substitutions have significant effects on substitution patterns. The success of a paradigmatic shift is not only a function of technological characteristics but also depends on change agents and many social dynamics. Such complexity requires analysis at several levels of granularity. We start with cognitive processes at the individual level using concepts from cognitive psychology and decision making under uncertainty and then move to interpersonal communications at the aggregate social level. We show that population heterogeneity generates different decision criteria and a social topology which greatly affect perceptions and the formation of expectations. The structure of interpersonal networks also explains how the relevance and credibility of information impact the critical mass dynamics of technology adoption. A more complete model accounting for social interactions provides a useful framework for understanding complex substitution patterns and reducing the risk of misreading the market.     

技术需求与智能制造技术创新——数字经济的导向性赋能机制

智能制造技术创新是持续推动制造业高质量发展的关键动力。为探究制造业技术需求、数字经济赋能对非市场与市场导向下智能制造技术创新的作用机制，基于技术创新需求拉动理论，引入数字经济赋能构建投入-产出两阶段模型。分析发现，当政府研发补贴较高时，劳动替代需求与智能制造技术创新投入呈倒U型相关，对智能制造研发投入产生挤出效应；以效率提升为主的技术市场需求通过影响企业智能制造技术创新投入，间接推动技术创新产出。有调节的中介模型检验表明，数字经济赋能正向调节市场导向的智能制造技术创新产出，但对非市场导向的技术创新不具赋能作用。在充分利用数字经济发展优势的同时，应依托需求拉动机制开发更多需求侧政策工具，进一步激发智能制造技术创新。     

Combined forecast process: Combining scenario analysis with the technological substitution model

Forecasts can be improved by combining separate forecasts obtained by different methods. The complementary nature of the scenario analysis and technological substitution models means that combining the two can obtain improved forecasts. The former has the strength of dealing with the uncertain future, while the later offers data-based forecasts of quantifiable parameters. This study thus proposes a process for combining the scenario analysis with the technological substitution model for discussing new generation technological developments. The proposed process not only has the strengths of scenario analysis, but also contains features that scenario analysis lacks, including predicting annual developments for future years, considering old technology development, and forecasting substitution of old technologies. This study uses the forecast of the market share of Fiber to the x in Taiwan over the next ten years as an example illustrating the proposed combined forecast process.     

Innovation diffusion with generation substitution effects

Markets of high technology products and services, such as telecommunications, are described by fast technological changes and rapid generational substitutions. Since the conventional modeling approaches that are based on diffusion models do not usually incorporate this important aspect into their formulations, the accuracy of the provided forecasts is consequently affected. The work presented in this paper is concerned with the development of a methodology for describing innovation diffusion, in the context of generation substitution. For this purpose, a dynamic diffusion model is developed and evaluated, based on the assumption that the saturation level of the market does not remain constant throughout the diffusion process but is affected by the diffusion of its descendant generation, as soon as the latter is introduced into the market. In contradiction to the conventional diffusion models, which assume static saturation levels, the proposed approach incorporates the effects of generation substitution and develops a diffusion model with a dynamic ceiling. The importance of such an approach is especially significant for markets characterized by rapid technological and generational changes. Evaluation of the proposed methodology was performed over 2G and 3G historical data and for a number of European countries, providing quite accurate estimation and forecasting results, along with important information regarding the rate of generation substitution.     

Intertemporal data and travel cost analysis

This paper considers the use of multi-year data in travel cost analysis. To exploit the information embedded within intertemporal data, two broad approaches are examined: multiple year cross sections and panel models. Multiple year cross sections can be used to detect trends, and to test for stability of behavior. Panel models can be used to control for unobservable factors that are individual specific. Unfortunately, the low intertemporal variability of travel cost data sets weakens the power of panel estimators. Using aggregate data from the Boundary Waters Canoe Area, the stability of demand processes over the 1980–1986 period is investigated, as well as the problems inherent in using panel estimators in travel cost analysis.     

The role of innovation and quality change in Japanese economic growth

This paper explores the use of time series data to isolate quality change in the Japanese economy using a hedonic procedure. We argue that the traditional approach to hedonic estimation based upon panel data sets of different brands in a given product area is extremely resource intensive and, thus, unlikely to be adopted by official statistical bodies outside of key areas, such as computers. This paper adopts a “top-down” approach to see whether more traditional measures of technical change, such as patents, can be used to separate pure inflation from quality change. If this is possible, it offers a much simpler route to estimate the role of quality change in economic growth and performance. In practice, we extend the analysis not only to include patents, but other forms of intellectual property that might reflect technology and attribute changes, such as designs, utility models and trademarks. We begin by taking a longer-term historical perspective, exploring the development of indigenous inventive capacity in Japan during the early years when R&D data are not available. It is possible to show that the rise in utility models pre-dates the main growth in patenting activity, suggesting the development in more low-level indigenous creative work prior to higher level inventive activity. The principal aim of this paper, however, is to demonstrate that it is possible to develop robust models to explain changes in the producer price index in Japan, which can then be used to re-examine Japanese growth performance over the period from about 1960. If the official Japanese statistical body has fully accounted for quality change in the price indices (i.e. produced fully quality-constant price deflators), then the official estimates of growth will be correct. However, we provide strong evidence that this is not the case. Changes in quality, proxied by the IP variables, are important determinants of prices in Japan over the period 1960 to 1995 as a whole. Indeed, we provide evidence that the true rate of growth of the Japanese economy, taking into account the rate of quality change, is significantly higher than that suggested in official statistics.     

Cointegration,dynamic structure,and the validity of purchasing power parity in African countries

The purpose of this paper is to test the validity of the purchasing power parity (PPP) in Africa in the context of a multivariate error-correction model. This approach allows for the consideration of long-run elasticities as well as the dynamics of the short-run adjustment of exchange rates to changes in domestic and foreign prices. Monthly data for fourteen African countries are used, and the period examined is 1973:4 through 2007:7 (i.e., 412 observations). Results from long-run cointegration analysis, short-run error correction models, persistence profile analysis and variance decomposition all confirm the validity of PPP in these moderate-to-high inflation countries, where estimates of half-life deviations from PPP are found to be outside the range suggested by Rogoff (1996).     

Technology forecasting for commodity projections: A case study on the effect of substitution by aluminum on the future demand for copper

This paper deals with the possible use of technology forecasting in commodity projection and, to a lesser extent, in resource allocation for research and development. As a specific example, technology forecasting was used to estimate the effect of substitution of copper by aluminum on the future demand of copper in 1980 and 1990. and to identify a future technology for extracting aluminum from clay; a technology which could be especially useful in the developing countries. Basic predictions were made for functional units of the major common end uses of copper and aluminum in 1980 and 1990, including electrical conductor and heat exchanger applications. The amounts of copper required in each application in 1980 and 1990 were estimated for three substitution scenarios. In the first of these, substitution is assumed to take place according to a logistic type function, resulting in a predicted copper demand of 3.70 million tons in 1980 and 4.91 million tons in 1990. In the second scenario, substitution is assumed to progress at past linear rates, resulting in a predicted copper demand of 4.3 million tons in 1980 and 6.41 million tons in 1990. In the third scenario, no further substitution is assumed, resulting in a predicted copper demand of 4.81 million tons in 1980 and 7.77 million tons in 1990. The effective date of the technology monitoring that produced these predictions is July 1974, and the predictions are current as of the date. The then current forecasts for copper demand made by the U.S. Bureau of Mines and other agencies using compound growth and regression models, corresponded to the unlikely scenario of no further substitution, and therefore needed correction in view of these anticipated technological changes.     

PERFORMANCE OF VARIOUS ESTIMATORS FOR CENSORED RESPONSE MODELS WITH ENDOGENOUS REGRESSORS

The paper reviews four approaches (substitution (SUB), control function (CF), system reduced form (SRF) and artificial instrumental regressor (AIR)) dealing with endogenous regressors in censored response models, and compares them through a simulation. Based on mean‐squared‐error type criteria, CF and AIR perform better than SUB and SRF; in terms of computation, however, SUB and CF are the easiest, closely followed by SRF. Although CF does well in both accounts, its assumptions are restrictive, and CF provides very different results from the other estimators when a real data set is used. Therefore, although the choice of an estimator among the four should be case‐specific, for practitioners, we would recommend SUB.