Applied Economics Journal <p>Applied Economics Journal (ISSN: 2586-9124) is a double blind peer-reviewed journal devoted to the applications of economic theories, concepts and methodologies to analyze well-defined research issues. It encourages empirical analysis, simulation, prediction and forecasting research. While it is aimed at academics and policy makers interested in the Thai and Asian economies, the journal also considers articles that deal with global issues. The primary criteria for selecting papers are originality, quality, and contribution to the field. The categories of articles include commentary, review articles, research articles and book reviews. &nbsp;AEJ is indexed in the Thai-Journal Citation Index Centre (TCI), IDEAS/RePEc, CAB Abstracts, Google Scholar, ASEAN Citation Index (ACI) and Emerging Sources Citation Index (ESCI). Two issues are published a year, in June and December. All articles are open access. No submission fee and page charge.</p> The Center for Applied Economics Research (CAER) en-US Applied Economics Journal 2586-9124 <p style="text-align: justify;">Submission of a manuscript to Applied Economics Journal will be taken to imply that the author(s) guarantee that the paper is an original work, has not been published, and is not being considered for publication elsewhere either in printed or electronic form. The author(s) have obtained permission from the copyright holder to reproduce in the article material not owned by them, that author(s) have acknowledged the source, and that this article contains no violation of any existing copyright or other third party right or any material of an obscene, indecent, libelous or otherwise unlawful nature and that the article does not infringe the rights of others. The author(s) will indemnify and keep indemnified the editors and Applied Economics Journal, Center for Applied Economics Research (CAER), Faculty of Economics, Kasetsart University against all claims and expenses. The author(s) agree that the publisher may arrange for the article to be published and sold or distributed on its own, or with other related materials, and could reproduce and/or distribute in printed, electronic or any other medium whether now known or hereafter devised, in all languages, and to authorize third parties to do the same.</p> Linear and Nonlinear Causality between Stock Market Volatility and the business Cycle in Iran <p>This paper surveys the relationship between stock market volatility and the business cycle in the Iranian economy, where both linear and nonlinear bivariate causality tests are used in the survey. The monthly data of the World Bank from 2000 to October 2016 is used in this survey. The results advocate that there is one-side linear causality between the business cycle and the stock market volatility, likewise, nonlinear relationship between the two mentioned variables are confirmed. It means that the results of the Granger causality in two-side analysis show that there is one-side linear relationship from business cycles to stock market volatility in Iran. On the other hand, by using a nonlinear method, the assumption of nonlinear causality from business cycles to stock market volatility was confirmed, while the results didn’t approve the assumption of linear and nonlinear causality from stock market volatility to business cycles. Therefore, to decision making in macroeconomic issues and investors in stock market, nonlinear relationships between macro-variables should be considered alongside linear causality, as it seems that the business cycles can have an impact on the stock market volatility in Iran, so, Investors can make their investment strategies in the stock market based upon the change in the business cycle.</p> Firouzeh Azizi Fahimeh Moradi ##submission.copyrightStatement## 2019-04-26 2019-04-26 26 1 1 13 Trade Openness and Spatial Distribution of Manufacturing Industries: Iranian Provincial Evidence <p>This paper aims to study the impact of trade openness on the spatial concentration of economic activities of manufacturing industries within the framework of New Economic Geography (NEG) theory. A three-step approach was used for testing the research hypothesis. Stationary test results of variables, in the first step, indicated that the variables are I (1). The results of the Pedroni panel cointegration test specified a long-run relationship between variables. In the third step, using GMM and fixed effects methods, the specified model were estimated for 28 provinces of Iran during 2004 - 2013. The findings show that trade openness has a negative and significant effect on the geographical distribution of manufacturing industries in the provinces of Iran. Indeed, the export promotion policies since the 1990s have led to the dispersion of manufacturing industries in the Iran provinces.</p> Mansour Ardeshiri Reza Moghaddasi Saeed Yazdani Amir Mohamadinejad ##submission.copyrightStatement## 2019-04-26 2019-04-26 26 1 14 29 The Information Flow Interpretation of Margin Debt Value Data: Evidence from New York Stock Exchange <p>This paper examines the heteroscedasticity in NYSE Composite index returns using margin debt value data from a sampling period of December 1996 to November 2017. Following Lamoureux and Lastrapes (1990), the lagged margin debt value is included in the conditional variance of GARCH and EGARCH models. The results of EGARCH estimates show that the ARCH effect vanishes and the total volatility persistence is most reduced, confirming that the margin debt value is a reflection of time dependence in the rate of new information arrival on&nbsp; stock market borrowing (i.e. margin borrowing). Further, the lagged margin debt value coefficient is negatively and significantly related to the conditional volatility. This implies that— when the new information pertaining to credit risk flows to the market, the investors adjust the risk&nbsp; downward (i.e. downward revision) as their repose to the flow of new information. However, GARCH estimates have shown to provide a weaker reflection of the effect of information pertaining to stock market borrowing (i.e. margin borrowing) on conditional volatility and therefore had little explanatory power of heteroscedasticity in the stock return data. Overall, the results suggest that the form of persistence of new information arrival on margin debt value data in the conditional volatility is a reflection of ARCH type of residual heteroscedasticity of stock return data of the New York Stock Exchange.&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</p> Chamil W Senarathne ##submission.copyrightStatement## 2019-04-26 2019-04-26 26 1 30 46 The Regional Dynamics of Economic Growth: Evidence from GMM Estimation in Turkey <p>Recently, a growing body of research has dealt with the causes of growth differences in the context of regional economies. It can be argued that such differences mostly arise from a variety of economic and structural determinants pertain to regional characteristics. This study investigates the effects of potential determinants of regional economic growth in Turkey. In this respect, we examine the impact of human capital, R&amp;D, exports, public investments, inflation and unemployment on per capita regional income across the 26 NUTS 2 regions for the 2008-2014 period. The results of the difference and the system GMM estimations show that human capital and R&amp;D are essential for economic growth at a regional level. According to the results, exports, public investments and inflation are also important determinants of regional economic growth. However, empirical results indicate an inverse relationship between regional growth and unemployment.</p> Mustafa Gömleksiz Serife Özsahin ##submission.copyrightStatement## 2019-04-26 2019-04-26 26 1 47 65 From Agriscience to Agribusiness: Theories, Policies and Practices in Technology Transfer and Commercialization (Innovation, Technology, and Knowledge Management) <p class="yiv0023895709ydp5b0a166yiv9503078463ydp650a5eeayiv5132335139ydp8b23ef58yiv5829594949msoplaintext" style="margin: 0cm; margin-bottom: .0001pt; text-align: justify; background: white;"><em><span style="font-size: 16.0pt; font-family: 'Cordia New',sans-serif; color: #1d2228;">“Agribusiness has assumed a greatly expanded role in driving innovation in agriculture over the past generation. The appearance of new scientific opportunities and an evolving set of strategies for protecting intellectual property have driven rapid growth in both upstream and downstream research investments, a frantic pace of merger and acquisition activity, and have induced major changes in how the public and private sectors interact. This volume brings together new evidences on the current functioning of the agriscience agribusiness system for generating and delivering agricultural technology.”</span></em></p> Greg Traxler ##submission.copyrightStatement## 2019-04-26 2019-04-26 26 1