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

Estimation and Inference in Econometrics

relationship. All subsequent studies confirmed it (see for example King and Levine, 1993, and the review in: Pagano, 1993). Goldsmith used a sample of 35 countries for the period between 1860 and 1963 to show the relationship between income and financial depth measured by the ratio between bank's assets and GDP. He also showed that in periods of rapid growth, financial depth grows faster than income. More details about measuring financial depth can be found in this paper. FINANCIAL DEVELOPMENT AND ECONOMIC GROWTH Velimir Šonje

/pdf/financial-development-and-economic-growth-1933kuo17q.pdf

Financial development and economic growth

Using a Vector Autoregression (VAR) approach, several hypotheses are re-examined suggested by the literature concerning the relationship between financial development and economic growth, investment and productivity. The models use quarterly time-series data from ten OECD countries and China. Innovation accounting or variance decomposition and impulse response function analysis is applied to examine interrelationships between variables in the VAR system and, therefore, differs from the more usual Granger causality approach. In particular, it examines the relationship between financial development proxied by total credit. At best, weak support is found for the hypothesis that financial development 'leads' economic growth.

Does financial development ‘lead' economic growth? A vector auto-regression appraisal

This study investigates the relationship between financial sector development and progress in reaching the Millennium Development Goals (MDGs). It assesses the contribution of countries' financial sector development to achieving the MDGs. The focus is on the relationships between financial development and economic welfare and growth, and the following four MDG-themes: Poverty, Education, Health, and Gender Equality. In doing so, the book reviews the theoretical channels, surveys existing empirical evidence - both cross-country and case study evidence, and provides new evidence. Financial Sector Development and the Millennium Development Goals finds that financial development is an important driver for economic welfare in that it reduces the prevalence of income poverty and undernourishment. In addition, new evidence is provided of a positive association between financial development and health, education, and gender equality.

https://openknowledge.worldbank.org/bitstream/handle/10986/7145/386880financia101official0use0only1.pdf?sequence=1

Financial Sector Development and the Millennium Development Goals

Agenor attempts to examine analytically and empirically the extent to which globalization affects the poor in low- and middle-income countries. He begins with a description of various channels through which trade openness and financial integration may have an adverse effect on poverty. However, the author also stresses the possible nonlinearities involved - possibilities that have seldom been recognized in the ongoing debate. Agenor then presents cross-country regressions that relate measures of real and financial integration to poverty. The regressions control for changes in income per capita and output growth rates, as well as various other macroeconomic and structural variables, such as the inflation tax, changes in the real exchange rate and the terms of trade, health and schooling indicators, and macroeconomic volatility. The author uses not only individual indicators of trade and financial openness but also a "globalization index" based on principal components analysis, and tests for both linear and nonlinear effects. The results suggest the existence of a nonmonotonic, Laffer-type relationship between globalization and poverty. At low levels, globalization appears to hurt the poor; but beyond a certain threshold, it seems to reduce poverty - possibly because it brings with it renewed impetus for reform. So, globalization may hurt the poor not because it went too far, but rather because it did not go far enough. This paper - a product of the Poverty Reduction and Economic Management Division, World Bank Institute - is part of a larger effort in the institute to study the impact of globalization on the poor in developing countries.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID636284_code170891.pdf?abstractid=636284&mirid=1&type=2

Does Globalization Hurt the Poor

In this paper we evaluate the contributions of human capital and financial development to economic growth in a panel of 82 countries covering 21 years. The main innovations in the paper stem from the fact that we use a translog production function as a framework for estimating the relationships among economic growth and factor inputs. The factor inputs considered are: labour, physical capital, human capital (deriving from endogenous growth theory), and a monetary factor (money or credit, deriving from the theory of money in the production function). The translog production function enables a richer specification of the relationships among growth and factor inputs, than the more commonly used Cobb–Douglas approach, as it allows for interactions among factor inputs. We find significant evidence of such interactions, suggesting that studies which ignore such interactions are likely to be misleading. Overall, our results suggest that financial development is at least as important as human capital in the growth process. Copyright © 2002 John Wiley & Sons, Ltd.

Human capital and financial development in economic growth: new evidence using the translog production function

This paper investigates the importance of political structure in the economic growth process, within a growth model. Based on a translog production function, the model incorporates human capital and financial variables, and is further augumented with variables that underpin key hypotheses on political structure. The model is estimated and tested using a comprehensive panel of 82 countries over 21 years. The main findings are four. First, we reaffirm that financial and human capital play an important role in economic growth as well as physical capital. Second, economies with greater political rights and civil liberties experience faster rates of per capita growth than do authoritarian regimes. Third, military conflict imparts a deleterious influence on economic growth. Fourth, we identify and provide unified evidence for the existence of a clear channel through which political structures do not merely affect the growth rate but more particularly the economic process through which growth occurs: societies with a higher degree of political rights and civil liberties use their factors of production more effectively. The implications of this study therefore are that political structure really matters for economic growth, and deserves as much attention as do human capital and financial variables. JEL Classification: A12, H11, O11, O57

Alun Dwyfor Evans

Papers

Human capital and financial development in economic growth: new evidence using the translog production function

Does Political Structure Really Matter? Evidence on Political Structure, Financial Development and Economic Growth #