International Knowledge Diffusion and Home‐bias Effect: Do USPTO and EPO Patent Citations Tell the Same Story?*

This paper estimates the international diffusion of technical knowledge using patent citations. We control for self‐citations and for procedural differences between patent offices using equivalent patents. We find that (1) there are clear biases in patent examination processes that generate citations in the two offices; (2) at the EPO there is a strong localization effect at the country level, and the size is comparable to that found at the USPTO; (3) technological fields have different properties of diffusion in the two patent offices that do not depend on a patent office bias; (4) using EPO data, the US is not the leading country in terms of citations made and received, as occurs at the USPTO.     

Private value of European patents

I examine the joint patent designation-renewal behavior of the European Patent Office (EPO) patent applicants during 1978-1996, using both nonparametric techniques and a parametric model. The European patents granted through the EPO are substantially more valuable than those through the national route. Value distribution of patents is highly skewed, and even more so for the EPO patent families. The value of patent rights increases with the economic size of the country and exhibits modestly increasing returns to scale. Model estimation also reveals significant institutional differences across EPO member countries in patent protection.     

An empirical analysis of patents flows and R&D flows around the world

In this article, we empirically investigate the effect of Research and Development (R&D) flows on patent flows around the world. We do this using an unbalanced panel consisting primarily of Organization for Economic Co-operation and Development (OECD) countries that have both patent and R&D expenditure information broken down by domestic and foreign sources. Our analysis shows that even among a fairly homogeneous group of countries, the sources of patents and R&D differ substantially. Using a dynamic panel framework, we find that domestic R&D per capita increases domestic patents per capita only for the European Patent Convention (EPC) countries that already have a decentralized approach to innovation. Foreign R&D per capita increases foreign patents per capita in all countries even though foreign R&D constitutes a very small fraction of total R&D. We find that some of these differences can be attributed to the locations of the patent applications, including those to the European Patent Office (EPO), United States Patent and Trademark Office (USPTO) and triadic patent applications to the EPO, USPTO and Japan Patent Office (JPO) simultaneously.     

Specification and testing of count data recreation demand functions

This article examines the effects of alternative formulations of count data recreation demand models on parameter estimates, model selection, and consumer surplus. The results indicate that large parameter and consumer surplus differences exists across the various count model formulations. More importantly, the results show that distributional assumptions, heteroscedastic functional forms, and overdispersion can have a substantial effect on consumer surplus estimates.     

Application of Sample Selection Model to Double-Bounded Dichotomous Choice Contingent Valuation Studies

Modeling households' behavior with the data from a contingentvaluation (CV) survey is often complicated by samplenon-response, which can cause non-response bias and sampleselection bias, leading to inconsistent parameter estimates and adistorted mean willingness-to-pay estimate. This paper reportsthe results of empirical tests for both biases using householdsurvey data in which the double-bounded dichotomous choice CVquestion involved the benefit of a tap water quality improvementpolicy in Korea. No non-response bias, but sample selection bias,is detected in the sample. To correct for sample selection bias,a sample selection model is employed. The authors also discusshow failure to correct for bias may distort aggregate benefitestimates.     

Universities and intellectual property rights in Southern European countries

This paper analyses and discusses the patenting activity of Public Research Organizations (PROs) in Southern European countries. Despite the importance of the topic, studies about the European experience are rare. By using an original database of “American” (USPTO) and “European” (EPO) patents held by PROs in Portugal, Spain, France, Italy and Greece, we observe that the number of university patents in these countries has not increased dramatically during the last years, despite a growing interest at both European and national level during the same period. However, differences do exist among countries in terms of number of granted patents and regulative frameworks. With regard to PROs patenting strategies, we argue that PROs should be progressively able to adopt a “balanced” approach, in order to achieve co-existence between the traditional mechanisms of the so-called “open research system” and the more recent concerns about intellectual property protection, technology transfer and regional development.     

The roots of inequality: estimating inequality of opportunity from regression trees and forests*

We propose the use of machine learning methods to estimate inequality of opportunity and to illustrate that regression trees and forests represent a substantial improvement over existing approaches: they reduce the risk of ad hoc model selection and trade off upward and downward bias in inequality of opportunity estimates. The advantages of regression trees and forests are illustrated by an empirical application for a cross-section of 31 European countries. We show that arbitrary model selection might lead to significant biases in inequality of opportunity estimates relative to our preferred method. These biases are reflected in both point estimates and country rankings.     

APPRAISING THE U.S. OUTPUT AND PRODUCTIVITY ESTIMATES FOR GOVERNMENT–WHERE DO WE GO FROM HERE?

Output and productivity estimates for U.S. government organizations are a useful management tool, and are of potential value for improving national income accounts. Real gross government product is currently estimated on the basis of labor input data. However, this imparts a downward bias to real GNP estimates since labor productivity of federal civilian employees has risen, according to Labor Department estimates begun in 1972, at an average annual rate of 1; percent since 1967. The estimates now cover almost 70 percent of the employees. The chief avenue for further improvement lies in refinement of the output indicators. Coverage of state and local government employees is spotty and needs to be expanded. The author also recommends a major effort to estimate public capital stocks in current and constant prices as a basis for measuring rental values, capital inputs, and productivity.     

Catholic schooling and further education

Using new estimation methods and data, I find that Catholic schooling substantially increases years of schooling by 0.42 to 0.47. The estimates are robust to various specifications that account for potential selection bias.     

Persistent media bias

The news media plays an essential role in society, but surveys indicate that the public views the media as biased. This paper presents a theory of media bias that originates with private information obtained by journalists through their investigations and persists despite profit-maximizing news organizations and rivalry from other news organizations. Bias has two effects on the demand for news. First, rational individuals are more skeptical of potentially biased news and thus rely less on it in their decision-making. This skepticism reduces demand and leads the news organization to set a lower price for its publication the greater is the bias it tolerates. Lower quality news thus commands a lower price. Second, bias makes certain stories more likely than others. Given their private information, journalists may bias their stories if their career prospects can be advanced by being published on the front page. News organizations can control bias by restricting the discretion allowed to journalists, but granting discretion and tolerating bias can increase profits if it allows journalists to be hired at a lower wage. Bias is not driven from the market by a rival news organization nor by a news organization with an opposing bias, and the profits of a high-bias news organization can be higher than the profits of a low bias one. Moreover, bias can be greater with competition than with a monopoly news organization. If individuals collectively choose regulation in place of their individual decision-making, bias increases the expected stringency of regulation.     

IMPACT OF COOPERATIVES MEMBERSHIP ON ECONOMY IN EASTERN OROMIA: THE CASE OF HARAMAYA AGRICULTURAL FARMERS’ COOPERATIVE UNION (HAFCU)

This study attempts to analyse the impact of cooperatives on the smallholders’ income, productivity, marketed surplus and saving in East Hararghe Zone of Haramaya District. The study is based on primary cross‐sectional data collected from cooperative member and non‐cooperative member household heads. The propensity score matching (PSM) estimates complemented by a bias correction matching (BCM) and Lewbel instrumental variable (IV) regression estimation shows that cooperatives have a positive impact on smallholders’ income and productivity. The findings have strong policy implications. The rural development of the country should work toward strengthening and expanding the existing rural organizations through training and capacity building programmes. It is important particularly establishing new rural‐based organizations that enable rural households to engage in business activities. Doing that may help reduce poverty and increase smallholders’ income, productivity, and capital accumulation.     

Research,Innovation And Productivi[Ty: An Econometric Analysis At The Firm Level

This paper studies the links between productivity, innovation and research at the firm level. We introduce three new features: (i) A structural model that explains productivity by innovation output, and innovation output by research investment: (ii) New data on French manufacturing firms, including the number of European patents and the percentage share of innovative sales, as well as firm-level demand pull and technology push indicators; (iii) Econometric methods which correct for selectivity and simultaneity biases and take into account the statistical features of the available data: only a small proportion of firms engage in research activities and/or apply for patents; productivity, innovation and research are endogenously determined; research investment and capital are truncated variables, patents are count data and innovative sales are interval data.

We find that using the more widespread methods, and the more usual data and model specification, may lead to sensibly different estimates. We find in particular that simultaneity tends to interact with selectivity, and that both sources of biases must be taken into account together. However our main results are consistent with many of the stylized facts of the empirical literature. The probability of engaging in research (R&D) for a firm increases with its size (number of employees), its market share and diversification, and with the demand pull and technology push indicators. The research effort (R&D capital intensity) of a firm engaged in research increases with the same variables, except for size (its research capital being strictly proportional to size). The firm innovation output, as measured by patent numbers or innovative sales, rises with its research effort and with the demand pull and technology indicators, either directly or indirectly through their effects on research. Finally, firm productivity correlates positively with a higher innovation output, even when controlling for the skill composition of labor as well as for physical capital intensity.     

EVIDENCE ON GENDER WAGE DISCRIMINATION IN PORTUGAL: PARAMETRIC AND SEMI‐PARAMETRIC APPROACHES

In this paper we consider several alternative approaches to analyze gender wage discrimination. Besides the traditional OLS estimator, we use two other approaches to control for sample selection bias problems: the parametric procedure suggested by Vella and Wooldridge, and the Li and Wooldridge semi‐parametric estimator. We study the case of Portugal, employing data from the European Community Household Panel. The results reveal that the discrimination estimates are sensitive to the different econometric approaches. In fact, when sample selection bias is taken into account, the discrimination values are reduced and are typically not significant.     

An international study of persistence in output: Parametric estimates using the data dependent systems approach

This paper parametrically obtains estimates of persistence in output using Pandit's (1977, 1982) Data Dependent Systems approach for modelling autoregressive and moving average processes. The estimates are based on over a century of annual data for the rate of change of output in nine industrialized countries. The sensitivity of estimates to various model selection criteria is examined. While persistence in output is found to be sensitive to model selection criteria, the output of all countries including the United States is found to have a substantial degree of persistence if the ARMA models are chosen according to the Schwarz Bayesian Criterion, but excluding the ARMA models whose moving average roots are near the unit root (which involves pile-up phenomenon). Moreover, the parametric estimates of persistence are shown not to have the known upward bias problem commonly associated with parametric estimates of persistence relative to nonparametric estimates.     

技术会聚对创新绩效的作用机制研究

随着社会经济快速发展,技术会聚备受关注。基于美国专利商标局授权的2 025项中国专利数据,利用负二项回归模型,探讨组织机构技术会聚程度对创新绩效的作用机制,并引入技术知识成熟度和技术知识流动性作为调节变量。研究结果表明：组织机构技术会聚程度与其创新绩效呈倒U型关系;组织机构技术知识成熟度削弱了技术会聚程度与创新绩效之间的关系;组织机构技术知识流动性削弱了技术会聚程度与创新绩效间的关系。研究结论可为组织机构提高创新绩效提供理论依据。     

On the measurement of patent stock as knowledge indicators

Most of the conventional indicators for measuring the amount of technological knowledge (TK) have so far been input-based indicators. Hence, there is growing need to develop output-based indicators, and accordingly some studies have been conducted thereon. However, previous research has adopted patent count or patent stock by simple count in measuring the amount of TK as output-based indicators. The principal problem with using this variable is that the value of individual patent is too heterogeneous. That is a large portion of these patent databases are either of little value or nothing at all. As a result, patent count or patent stock by simple count cannot be seen as a suitable measure of TK.In this study, we attempted to resolve the value-heterogeneity problem in measuring patent stock. The notion of citation-based patent stock (CPS) and valuation-based patent stock (VPS) is proposed in this paper and the calculation method is described in detail. In CPS, the economic value of individual patent is assumed to be proportional to the number of citations received from other patents. And in VPS, the economic value of individual patent is derived from the value distribution of patents registered in some cohort by manipulating the patent renewal data. We validated the indicators by comparing them with the usual input-based indicators and by analyzing the relationships between them and the productivity growth empirically.     

Quantile regression with sample selection: Estimating women's return to education in the U.S.

This study uses quantile regression techniques to analyze changes in the returns to education for women. The data used is the March Current Population Survey for the years 1968, 1973, 1979, 1986 and 1990. The first step in estimating the single (linear) index selection equation uses Ichimura's (1993) semiparametric procedure. To correct for an unknown form of a sample selection bias in the quantile regression, the second step incorporates a nonparametric method, using an idea similar to one developed by Heckman (1980) and Newey (1991) for mean regression, and Buchinsky (1998) for quantile regression.  The results show that: (a) the returns to education increased enormously for the younger cohorts, but very little for the older cohorts; (b) in general the returns are higher at the lower quantiles in the beginning of the sample period and higher at the higher quantiles by the end of the sample period; (c) there is a significant sample selection bias for all age groups at almost all quantiles; (d) toward the end of the sample period there is a significant convergence of the returns at the various quantiles, especially for the younger cohorts and age groups; and (e) the semiparametric estimates of the selection equation are considerably different from those obtained for a parametric probit model.     

The Innovation‐R&D Nexus in an Emerging Economy: Evidence from the Indian Manufacturing Sector

While R&D is considered an important input for innovation, its relationship with the output of the innovation process continues to remain enigmatic, especially in developing countries with low levels of domestic research. Using patents and knowledge capital stock as proxies for the output and input of the innovation process, we study their nexus in the emerging economy of India using a large sample of manufacturing firms over the period 2001–2010. Using a specification that addresses the problem of ‘excess zeroes’ in count data, the firm's non‐technical knowledge stock as an additional factor of the success with which R&D transforms into patents, and a linear feedback mechanism that yields consistent estimators, we find that a one unit increase in knowledge capital likely raises expected patent count by only about 4.3% at most. Further, although patenting experience, resource access and knowledge spillovers are strongly significant in explaining patent counts, the magnitude of these effects is marginal at best. In brief, evidence for the knowledge production function is rather weak even in the context of a dynamic developing economy.     

基于专利存续期的企业和研究机构专利价值比较研究

本文通过引入存续期未终止的专利,改进了传统以存续期为基础的专利价值模型,并使用该模型计算了我国1985—2009年间企业和研究机构的发明专利价值。通过对比发现,我国研究机构的平均专利价值显著低于企业。进一步回归分析发现,研究机构的研发资源占有量对专利价值并没有显著的正向作用,相反,企业占有较多的研发资源则有助于提高专利价值。在研发资源的联合配置方面,研究机构间合作研发下的专利价值也低于企业间的合作。     

The Effect of Protest Votes on the Estimates of WTP for Use Values of Recreational Sites

Contingent valuation studies are often characterized by a considerable number of protest responses, which may cause selectivity bias on the final estimates for WTP. Sample selection models can detect and – if necessary – correct selectivity bias. In economic applications where the relevant dependent variable is continuous, sample selection models are generally estimated using Heckman's 2-step method rather than the FIML estimator. Either method has its own drawback: computational complexity for the FIML method, susceptibility to collinearity problems for the 2-step method. Using data on valuation of forest resources for recreational use, we analyse the performance of the two estimators. In this application, given the presence of some collinearity, the FIML is preferred to the 2-step method. A procedure is outlined to deal with selectivity problems in similar settings.