Quantitative Economics

This paper models and predicts how the strengthening of intellectual property (IP) protection will impact R&D in developing economies. International agreements such as TRIPs and free trade agreements are enhancing the level of international control on IP. This is changing deeply the R&D environment in developing economies by restraining illegal channels of knowledge accumulation such as imitation, reverse engineering and piracy. An asymmetric and non-cooperative two-stage (R&D-Production) game is proposed to model a developing market where two local firms compete with a more innovative foreign firm. Equilibrium R&D expenditures and profits of the competing firms are compared for different levels of: market technology, technological gaps and IP protection. The proposed model shows clearly that a stringent enforcement of IP agreements will dramatically decrease the innovative abilities of developing economies especially in high technological sectors. The maintain and increase of their...

This paper provides a quantitative study of the economic effects of a stylised simulation of trade liberalisation for Ireland using the GTAP model. The experiment incorporates the liberalisation of agricultural, manufacturing and services trade as well as measures to improve trade facilitation. The simulation is implemented against a baseline projection of the Irish and world economy over the next decade. Overall, Ireland's welfare will increase as a result of further trade liberalisation, with particularly strong gains from services liberalisation. The industrial liberalisation scenario also generates positive gains to Ireland, while agricultural liberalisation has a slightly negative effect on the overall economy.

Many growth analysts have argued that more equal patterns of landownership and the supremacy of industry over agriculture were associated with the rise of mass public education systems during the late eighteenth and early nineteenth centuries. The theoretical framework of this argument relies mainly on the so-called capitalskill complementarity hypothesis that agricultural land and industrial capital are characterized by different levels of complementarity with human skills. Thus, landowning elites were often reluctant to promote and support public education, while rising capitalists were much more in favour of a better-educated workforce and promoted major educational reforms. This paper seeks to provide some of the first empirical evidence of a significant positive relationship between more equitable distribution of landholdings and the development of literacy in late nineteenth-century Greece, using data from the Censuses of 1870 and 1879. Our estimates largely confirm previous findings of a positive and significant linkage between people's access to land and literacy rates. On the contrary, labour concentration in the farm sector (the agriculture trap) has been found to be negatively and significantly related to literacy. These results remain robust after controlling for such other socioeconomic factors as marital status, family size, urbanization, ethnicity, religion, students' attainment and teachers' availability. called geography hypothesis, which holds that climatic and geographical conditions are responsible for the significant variations in economic performance between countries and regions (Bloom &

Happiness is considered to be one of the ultimate goals of life. This paper studies the happiness of Indian college and university students aged between 18 and 24 years. It attempts to answer whether and to what extent happiness of a student is significantly related to aspects of social life such as time spent with family, friends, being in a relationship, logging into social networking sites; academic factors such as job prospects of the chosen field of study and academic environment; and other personal factors such as health condition, over thinking or dwelling on past bad memories, addiction to tobacco/drug/alcohol. Moreover, this paper also inquires about the We are thankful to the anonymous reviewers for their valuable comments. We are also thankful to Anamika Sen, Isha Mallik, Sayantan Baidya, and Esha Dwibedi for their valuable suggestions and contribution in the data collection.

Recent advancements in technology have led to wide availability of highfrequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models. use the high frequency data to analyze the competition, liquidity and volatility between NSE and Bombay Stock Exchange (BSE). Chakraborty and Jain (2005) use high-frequency data from NSE to compute the spread-to-tick ratio. Goudarzi and Ramanarayanan (2010) study the performance of asymmetric GARCH models on BSE500. studies the model selection and forecasting accuracy of various GARCH models on NIFTY and BSE Sensex. Numerous studies have documented asset the presence of non-trivial jump component on the observed path of increasingly finer-sampled processes, see Ait-Sahalia and Jacod , , and . There is no work on jump detection in the Indian market.

This paper is concerned with the decomposition of change in poverty into growth and inequality components. A new decomposition procedure is derived using an axiomatic approach. This methodology is applied to explain changes in poverty in Thailand during the years 1988, 1990, 1992 ...

Revolutionary developments in the field of big data analytics and machine learning algorithms have transformed the business strategies of industries such as Banking, Financial Services, Asset Management, and e-Commerce. The most common problems these firms face while utilizing data are errors, anomalies and missing values in their dataset. The major objective of the present study is to impute fundamental data that is missing in the financial statements under a multivariate framework. We use the 'Multiple Imputation by Chained Equations' (MICE) frame work to impute fundamental data by utilizing the interdependency among the variables and also complying with the accounting rules. Our proposed MICE framework utilizes the Expectation Maximization methodology in two stages with initial values based on predictive mean matching in the first stage and resolving financial constraints in the second stage to provide multiple solutions for a given line item. The MICE methodology is less time consuming relative to other techniques and allows us to implicitly enforce accounting constraints.

Female work participation in West Bengal is one of the lowest among all the states in India. However, it varies widely across the state's 341 blocks. An analysis of some block level characteristics based on Census 2001 data show that female work participation varies inversely with the ...

Microeconomic theory is concerned with the behaviour of individual economic agents (consumers or firms) and eventually leads to a theory of aggregate economic outcomes for groups of individuals. Individual consumers set out to maximize utility and their preferences are represented by a utility function. They choose their consumption bundle in a manner that maximizes utility subject to a budget! wealth constraint. Their behaviour often takes the form of constrained maximization wherein the individual agent chooses from some specified set of options so as to maximize some objective function. Likewise, firms are guided by the motive of profit maximization subject to technology and production possibilities. Microeconomic theory, after modeling for individual behaviour, eventually leads to a theory of economic outcomes. In other words, choices that individuals make and the ways in which their actions affect each other is addressed using equilibrium analysis. Equilibrium is a situation wherein individual agents do not change their behaviour/actions in response to actions by others.

In this paper we explore inference on regression coefficients in semi parametric multinomial response models. We consider cross sectional, and both static and dynamic panel settings where we focus throughout on point inference under sufficient conditions for point identification. The approach to identification uses a matching insight throughout all three models and relies on variation in regressors: with cross section data, we match across individuals while with panel data we match within individuals over time. Across models, IIA is not assumed as the unobserved errors across choices are allowed to be arbitrarily correlated. For the cross sectional model estimation is based on a localized rank objective function, analogous to that used in Abrevaya, Hausman, and Khan (2010), and presents a generalization of existing approaches. In panel data settings rates of convergence are shown to exhibit a curse of dimensionality in the number of alternatives. The results for the dynamic panel da...

In the recent years, the burgeoning non-performing assets (NPAs) have become a matter of concern and scrutiny in India as the surge in NPAs impinge on the credit services of the banks, make the banks vulnerable to external shocks, leave them with less cushion in case of idiosyncratic shocks and thus, leading to the abrasion of their productive capital. In this backdrop, some very normative questions become inevitable. How has the technical efficiency of the banks in India changed over time especially after the asset quality review, 2016? How does undesirable output like nonperforming assets (NPA) impact the technical efficiency of banks in India? Does technical efficiency have anything to do with the ownership of banks? These are some of the questions we endeavour to answer through our study by employing three cornerstone methodologies namely DEA, Malmquist productivity index and SFA in the banking sector for the period 2014-2020.The results obtained from employing DEA and SFA both points toward the heterogeneity in the technical efficiency of public sector banks and private sectors banks operating in India. The results obtained from DEA are majorly threefold. Firstly, private sector banks have fared better than the public sector banks, while the SFA scores show that the public sector ownership promotes efficiency. Secondly, the technical efficiency of public sector banks has consistently been falling from 2014 to 2017 only to rise in the later years, evidence corroborated by the SFA scores also. This trend is in line with the slew of measures adopted by the government and RBI like AQR and mergers of banks subsequently. Although according to the Malmquist productivity decomposition results, we find that productivity of banks have been falling for the period 2014-2020. Thirdly, the non-performing assets are detrimental for the efficiency of the banks. Like DEA, the SFA results also shows the presence of technical inefficiency in the Indian banking sector and a similar trend in the technical efficiency wherein the scores decline from 2014 through 2017 and then they rise subsequently.

This paper studies identification of latent utility functions in multiple discrete choice models in which there may be endogenous explanatory variables, that is explanatory variables that are not restricted to be distributed independently of the unobserved determinants of latent utilities. The model does not employ large support, special regressor or control function restrictions, indeed it is silent about the process delivering values of endogenous explanatory variables and in this respect it is incomplete. Instead the model employs instrumental variable restrictions requiring the existence of instrumental variables which are excluded from latent utilities and distributed independently of the unobserved components of utilities. We show that the model delivers set identification of the latent utility functions and we characterize sharp bounds on those functions. We develop easy-to-compute outer regions which * This paper is a revised version of the February 2011 CeMMAP working paper CWP06/11. We thank seminar participants at Brunel University, CeMMAP, CREST, Harvard/MIT, The Institute for Advanced Studies (Vienna), UC Berkeley, UCLA, USC, and the University of Manchester, as well as audiences at the September 2010 CIREQ conference on revealed preferences and partial identification, the 21 st EC 2 conference held in Toulouse in December 2010, and the December 2011 workshop on consumer behavior and welfare measurement held at the IFS in London for comments and discussion. We especially thank Francesca Molinari for very helpful and detailed discussion on our use of random set theory.

This study highlights the importance of the information contained extreme value ratios (or returns) in the volatility estimation of financial assets. Most popular extreme value estimators like Parkinson (1980), Garman Klass (1980), Rogers Satchell (1991) and Yang Zhang (2000) use a subset of all available extreme value ratios but not the full set. We examine if there are other extreme value ratios which contain more information than the most widely used ratios. This study shows empirically how much information is contained in various extreme value ratios of financial assets, using both real and simulated data. Using information theory, we find out their variability in relation to a uniform distribution in each quarter. We then rank them using the Kullback-Leibler metric (in accordance with a scoring methodology we developed in this study) to ascertain which set of ratios are more variable than others and thus may provide better estimation in computing volatility. We also calculate the rank of the matrix to identify the set of linearly independent ratios, for ascertaining the number of ratios that would be enough to generate a class of volatility estimators. The empirical results demonstrate that the need for incorporating other ratios in volatility estimation. We also observe that each dataset has other more informative ratios which are uniquely attributed to that dataset.

for useful comments and corrections. We thank Ivan Fernández-Val for assistance in replicating the results of Angrist et al. (2006). A previous version of this paper circulated under the title \Interval Estimation of Potentially Misspecified Quantile Models in the Presence of Missing Data." The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peerreviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We introduce a computational technique-precomputation of integrals-that makes it possible to construct conditional expectation functions in dynamic stochastic models in the initial stage of a solution procedure. This technique is very general: it works for a broad class of approximating functions, including piecewise polynomials; it can be applied to both Bellman and Euler equations; and it is compatible with both continuous-state and discrete-state shocks. In the case of normally distributed shocks, the integrals can be constructed in a closed form. After the integrals are precomputed, we can solve stochastic models as if they were deterministic. We illustrate this technique using one-and multi-agent growth models with continuous-state shocks (and up to 60 state variables), as well as Aiyagari's (1994) model with discrete-state shocks. Precomputation of integrals saves programming efforts, reduces computational burden, and increases the accuracy of solutions. It is of special value in computationally intense applications. MATLAB codes are provided.

After 2003, the growth of equity prices in emerging markets in Asia, Latin America and Europe has been considerably higher in comparison with developed markets and, therefore, these markets have become the focus of attention of investors, the financial press, and researchers. These markets are needed to be studied separately because features of these markets are different from a developed market: on the one hand, they are hypersensitive to investors' sentiments and, on the other, equity returns are predictable by past observations. Unfortunately, common asset pricing models cannot explain such predictability in stock returns. The factor which is responsible for such predictability and hence the nonrandom behavior of the stock return can be accounted for in an asset pricing model. Based on this observation, the present paper proposes a generalization of the conventional asset pricing model. However, the framework would be applicable to all types of markets ranging from strictly efficient to inefficient.

How much additional tax revenue can the government generate by increasing the level of labor income taxes? In this paper, we argue that the degree of tax progressivity is a quantitatively important determinant of the answer to this question. To make this point, we develop a large scale overlapping generations model with single and married households facing idiosyncratic income risk, extensive and intensive margins of labor supply, as well as endogenous accumulation of human capital through labor market experience. We calibrate the model to U.S. macro, micro, and tax data and characterize the labor income tax Laffer curve for various degrees of tax progressivity. We find that the peak of the U.S. Laffer curve is attained at an average labor income tax rate of 58 % . This peak (the maximal tax revenues the government can raise) increases by 7 % if the current progressive tax code is replaced with a flat labor income tax. Replacing the current U.S. tax system with one that has Denmark&...

We examine the Economic Policy Uncertainty (EPU) transmission over the Exchange Rate Volatility (ERV) for 8 Emerging Market Economies (EME) using the recent panel VAR methodology of Abrigo and Love (Stata Journal 16:778–804, 2016). The econometric investigation reveals that: (a) both domestic and US-EPU shocks exert positive effects on the ERV, (b) the contribution of the US-EPU to the ERV fluctuations overcomes the own EPU’s share, (c) the ERV acts as a possible transmission channel of the US-EPU to the domestic economic activity, (d) the domestic EPU increases in response to a higher US-EPU and vice versa and (e) the latter is surprisingly and markedly sensitive to EME macroeconomic conditions. Our findings are robust to different sensitivity analyses, provide novel insights into EPU international spillovers, and have interesting policy implications for EME decisions makers and investors.

Prediction markets for future events are increasingly common, and they often trade several contracts for the same event. This paper considers the distribution of a normative risk-neutral trader who, given any portfolio of contracts traded on the event, would choose not to reallocate that portfolio of contracts even if transactions costs were zero. Because common parametric distributions can con ‡ict with observed prediction market prices, the distribution is given a nonparametric representation together with a prior distribution favoring smooth and concentrated distributions. The paper …nds posterior modal distributions for popular vote shares of the U.S. Presidential candidates in the 100 days leading up to the elections of 1992, 1996, 2000 and 2004, using bid and ask prices on multiple contracts from the Iowa Electronic Markets. On some days the distributions are multimodal or substantially asymmetric. The derived distributions are more concentrated than the historical distribution of popular vote shares in presidential elections, but do not tend to become more concentrated as time to elections diminishes.

This paper gives a relatively simple, well behaved solution to the problem of many instruments in heteroskedastic data. Such settings are common in microeconometric applications where many instruments are used to improve efficiency and allowance for heteroskedasticity is generally important. The solution is a Fuller (1977) like estimator and standard errors that are robust to heteroskedasticity and many instruments. We show that the estimator has finite moments and high asymptotic efficiency in a range of cases. The standard errors are easy to compute, being like White's (1982), with additional terms that account for many instruments. They are consistent under standard, many instrument, and many weak instrument asymptotics. Based on a series of Monte Carlo experiments, we find that the estimators perform as well as LIML or Fuller (1977) under homoskedasticity, and have much lower bias and dispersion under heteroskedasticity, in nearly all cases considered.

We examine the "home bias" of knowledge spillovers (the idea that knowledge spreads more slowly over international boundaries than within them) as measured by the speed of patent citations. We present econometric evidence that the geographical localization of knowledge spillovers has fallen over time, as we would expect from the dramatic fall in communication and travel costs. Our proposed estimator controls for correlated fixed effects and censoring in duration models and we apply it to data on over two million patent citations between 1975 and 1999. Home bias is exaggerated in models that do not control for fixed effects. The fall in home bias over time is weaker for the pharmaceuticals and information/communication technology sectors where agglomeration externalities may remain strong.

We examine the safe haven property of gold for stock and bond markets of G-7 countries. In doing so, we use the novel vector autoregressive for value-at-risk and the cross-quantilogram methods. These quantile-dependence measures help to examine how gold returns react to stock/bond returns when the markets are in a bearish state. The gold market is comparatively less sensitive to bond market innovations and more sensitive to stock market innovations. The tail dependence analysis, through cross-quantilogram, indicates that stock/bond returns significantly and positively spillover to the gold markets when both markets are in a bearish state. Furthermore, the findings of time-varying quantile dependence analysis, obtained by recursive sample estimations, are analogous to the full sample results. Hence, the evidence suggests that gold does not act as a safe haven for the stock and bond markets. Implications of the results are discussed.

This study empirically estimated the long-run and short-run impact of federal government human capital spending on human capital development in Nigeria. The study was motivated by the fact that despite growth in public spending in the past decade Nigeria still ranks low in human capital development. Time series data from 1990-2015 was collected and autoregressive distributed lag (ARDL) and Bounds test were used to estimate the short-run and long-run relationships respectively. The Bounds test was used to determine that a long-run relationship exists between Human Development Index (HDI) and government human capital spending while controlling for macroeconomic state of the economy using economic growth and inflation rate. The study finds that 1-year and 2-year lags of government recurrent education expenditure has weak significant negative impact on HDI rather than the expected positive impact. Only government recurrent health spending has positive impact on human capital development up to the 2-year lag. The speed of adjustment of the short-run relations is 41% significant at 5% level. The results demonstrated that both in the long and short run, government health spending has remained positive but to a very large extent insignificant to human capital development in Nigeria; whereas government education spending has not produced the desired positive impact on human capital development in Nigeria. This accounts for the low HDI of Nigeria over the years. The study therefore concludes that human capital development could be achieved through more efficient health spending in Nigeria. This study therefore strongly recommends that federal government should raise substantially the level of capital spending on education and health in order to achieve meaningful human capital development in Nigeria.

Electronic copy available at: http://ssrn.com/abstract=1792798 A Nonparametric Analysis of Black-White Differences in Intergenerational Income Mobility in the United States DebopamBhattacharya∗ University of Oxford Bhashkar Mazumder Federal Reserve Bank of Chicago ...

The main objective of the paper is to estimate the dynamic interrelation among
the macroeconomic variables viz., real output, real money, price, real interest rate
and real effective exchange rate using monthly data for India covering the period
from 1991:1 to 2007:12 using ARDL approach to cointegration.
The bounds test revealed that there exists a long-run relation between real
output, real money supply, real interest rate and exchange rate when the price
variable was the dependent variable. However, reverse cointegration relationships
were not noticed when the real output, real money supply and real interest rate were
the dependent variables. However, some evidence was observed on exchange rate
being influenced in the long-run by the selected macroeconomic variables.
The short-run causality confirmed bidirectional causality between real output
and money and a unidirectional causality running from real interest rate to real
output was found. The level of prices and exchange rate were found independent to
the changes in real output. The exchange rate and interest rate were found to be
independent to changes in money. Further, it was noticed that the price is caused by
output, money and interest rate where as causality does not seem to run from real
exchange rate to level of prices. The causality was found to be neutral from output,
money, price, and exchange rate on real interest rate. Finally, it was found that
output, money, price and interest rate has no effect on exchange rate in the short-run.

We present a fast and accurate computational method for solving and estimating a class of dynamic programming models with discrete and continuous choice variables. The solution method we develop for structural estimation extends the endogenous grid-point method (EGM) to discrete-continuous (DC) problems. Discrete choices can lead to kinks in the value functions and discontinuities in the optimal policy rules, greatly complicating the solution of the model. We show how these problems are ameliorated in the presence of additive choice-specific independent and identically distributed extreme value taste shocks that are typically interpreted as "unobserved state variables" in structural econometric applications, or serve as "random noise" to smooth out kinks in the value functions in numerical applications. We present Monte Carlo experiments that demonstrate the reliability and efficiency of the DC-EGM algorithm and the associated maximum likelihood estimator for structural estimation of a life-cycle model of consumption with discrete retirement decisions.

We examine a theoretically robust but previously undocumented issue of what drives foreign portfolio investments into emerging markets. Foreign institutional investors (FIIs) are often blamed as fair-weather friends who pull out their investment at the first sign of trouble. Using a bottom-up approach, we explore this possibility. We demonstrate the influence of the firm-specific factors such as size, book to market ratio, the riskiness of the stocks, stock prices, dividend yield, liquidity, leverage, and earnings on the FII ownership. We find no evidence to show foreign investors as fair-weather friends. Instead, they are smart traders who follow a diligent investment strategy. We suggest reforms in corporate governance and improvement in financial fundamentals of the companies to attract FII ownership.

This lecture aims to sensitize the new generations of economists to the fact that it is time to neutralize the mainstream economic language that imposes meaning and prescribes a truth. As a result, it is an obstacle to deepening the knowledge of the social nature of economic life in the real world. It is not a question of opposing the contemporary mainstream economic language by creating a new one under the mirror game, but of creating different writing styles by finding one's own being and overcoming the lost time, as did Marcel Proust in his novel In Search of Lost Time. The journey from the economist man who is driven by publication to the man economist who takes pleasure in writing will be long and arduous, but it is worth the effort. Fashion fades, only style remains the same. As René Girard noted in his last interview, the success of fashionable authors quickly fades just after their deaths.

This study empirically estimated the long-run and short-run impacts of federal government human capital spending on human capital development in Nigeria. The study was motivated by the fact that despite growth in public spending in the past decade, Nigeria still ranks low in human capital development. Time series data from 1990-2015 was collected and autoregressive distributed lag (ARDL) was used to estimate the short-run impact and the Bounds test was used to show that a long-run relationship exists between Human Development Index (HDI) and government human capital spending while controlling for macroeconomic state of the economy using economic growth and inflation rate. The study finds that 1-year and 2-year lags of government recurrent education expenditure have weak significant negative impact on HDI rather than the expected positive impact. Only government recurrent health spending has positive impact on HDI up to the 2-year lag. The speed of adjustment of the short-run relation is 41% significant at 5% level. The results reveal that both in the short and long run, government health spending impacted positively, though to a very large extent insignificant, on human capital development in Nigeria but not so with government education spending. This accounts for the low HDI of Nigeria. The study therefore concludes that human capital development could be achieved through more efficient health spending in Nigeria. This study therefore strongly recommends that federal government should raise substantially the level of capital spending on education and health in order to achieve meaningful human capital development in Nigeria.

This paper presents identification and estimation results for a flexible state space model. Our modification of the canonical model allows the permanent component to follow a unit root process and the transitory component to follow a semiparametric model of a higher‐order autoregressive‐moving‐average (ARMA) process. Using panel data of observed earnings, we establish identification of the nonparametric joint distributions for each of the permanent and transitory components over time. We apply the identification and estimation method to the earnings dynamics of U.S. men using the Panel Survey of Income Dynamics (PSID). The results show that the marginal distributions of permanent and transitory earnings components are more dispersed, more skewed, and have fatter tails than the normal and that earnings mobility is much lower than for the normal. We also find strong evidence for the existence of higher‐order ARMA processes in the transitory component, which lead to much different esti...

The objectives of this research were to determine: 1) the interest of young entrepreneurs in the district of Percut Sei Tuan, Deli Serdang Regency. 2) the influence of youth personalities, environment, and demography towards the interest of youth Entrepreneurship in the district of Percut Sei Tuan, Deli Serdang regency. Techniques used in the sampling was Franc Lynch. Research samples were taken from the youth in the district of Percut Sei Tuan aged from 18-30 years old, with 96 respondents obtained randomly. Data collection techniques used was primary, using questionnaires and a Likert scale on each question. The research method used was a survey. While for the data analysis technique a descriptive test and multiple linear regression were used. The result of this research revealed that: 1) Interest entrepreneurial youths in the district of Percut Sei Tuan in Deli Serdang area is very positive 2) Self efficacy, Achievement Needs, Availability Information, Networking, Access to Capit...

We study monopolistic pricing, with a capacity constraint, of a good that loses its value after three periods. In each period a continuum of buyers, each of whom might be one of two types, enter. Each of the buyers chooses either to make a purchase as soon as they enter, or to wait for a lower price. The price path is found to be strictly non-decreasing, u-shaped or horizontal for different proportions of buyers with a higher willingness to pay. Any strategy involving ‘final sales’ is non-optimal. The predictions are empirically tested.

Strategic interaction parameters characterize the impact of actions of one economic agent on the payoff of another economic agent, and are of great interest in both theoretical and empirical work. In this paper, by considering econometric models involving simultaneous discrete systems of equations, we study how the information available to economic agents regarding other economic agents can influence whether or not these strategic information parameters can be inferred from the observed actions. We consider two extreme cases: the complete information case where the information sets of participating economic agents coincide and the incomplete information case where each agent's payoffs are privately observable. We find that in models with complete information, the strategic interaction parameters are more difficult to recover than they are in incomplete information models. We show this by exploring the Fisher information (from standard statistics literature) for the strategic interaction parameters in each of these models. Our findings are that in complete information models, the statistical (Fisher) information for the interaction parameters is zero, implying the difficulty in recovering them from data. In contrast, for incomplete information models, the Fisher information for the interaction parameters is positive, indicating that not only can these parameters be relatively easy to recover from data, but standard inference can be conducted on them. This finding is illustrated in two cases: treatment effect models (expressed as a triangular system of equations) and static game models.

This paper explores the problem of empirical welfare-analysis in multinomial choice settings, allowing for completely general consumer-heterogeneity and income-e¤ects. We present results on welfare-analysis under three practically important scenarios, viz., (i) simultaneous pricechange of multiple options, (ii) introduction/elimination of a choice-alternative, and (iii) choice among non-exclusive goods. Our results do not follow from Bhattacharya (Econometrica, 2015). In program-evaluation contexts, these results would enable estimation of compensated programe¤ects, i.e., how much the subjects themselves value the program, and the resulting deadweight loss. Welfare-analysis under income-endogeneity is also brie‡y discussed. The methods are illustrated with hypothetical policy experiments using survey data from India on teenagers who make the choice between school, work and home-stay.

The results showed that the number of poor people and government expenditures from the aspect of health funds had a significant effect on the HDI. While open unemployment and government spending from the aspect of education fund did not significantly affect the Human Development Index. The success of the economic development of a region can be seen from the high economic growth, with the increase of economic growth is expected also can improve the welfare of society and increase human development with indicator of Human Development Index (HDI). _________________________________

Imposing equilibrium restrictions provides substantial gains in the estimation of dynamic discrete games. Estimation algorithms imposing these restrictions -- MPEC, NFXP, NPL, and variations -- have different merits and limitations. MPEC guarantees local convergence, but requires the computation of high-dimensional Jacobians. The NPL algorithm avoids the computation of these matrices, but -- in games -- may fail to converge to the consistent NPL estimator. We study the asymptotic properties of the NPL algorithm treating the iterative procedure as performed in finite samples. We find that there are always samples for which the algorithm fails to converge, and this introduces a selection bias. We also propose a spectral algorithm to compute the NPL estimator. This algorithm satisfies local convergence and avoids the computation of Jacobian matrices. We present simulation evidence illustrating our theoretical results and the good properties of the spectral algorithm.

Very few other issues in Indian economic development has generated so much debate than the measurement of total factor productivity (TFP) growth in Indian manufacturing. This debate has intensified following the major economic reforms in 1991. Using three different techniques – growth accounting (non-parametric), production function accounting for endogeniety (semi-parametric) and stochastic production frontier (parametric) – the paper computes the TFP growth of Indian manufacturing for both formal and informal sectors from 1994-95 to 2005-06. The results indicate that the TFP growth of formal and informal sector has differed greatly during this period and that the estimates are sensitive to the technique used. This suggests that any inference on productivity growth in India since the economic reforms of 1991 is conditional on the method of measurement used, and that there is no unambiguous picture emerging on the direction of change in TFP growth in post-reform India.

A simple three-sector general equilibrium model has been developed with both male and female labour and factor market distortions. The effects of different liberalized economic policies have been examined on the gender-based wage inequality. The analysis finds that credit market reform and tariff reform produce favourable effects on the wage inequality while the liberalized investment policy becomes counterproductive. These results have important policy implications for a small open developing economy. ♣ The authors are thankful to Prof. Ishita Mukhopadhyay for her helpful comments on an earlier version of the paper. The usual disclaimer, however, applies.

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