UČINAK TEČAJA I CARINSKE UNIJE NA TRGOVINSKU BILANCU SIROVINA TURSKE S EU (15)

This paper investigates the short-run and long-run impact of exchange rate and customs union on the trade balance at commodity-group level of Turkey with EU (15). Bounds testing approach is employed where a new strategy in the model selection phase is adopted ensuring that optimal model is selected from those models satisfying both diagnostics and cointegration. Results indicate that in the short-run exchange rate matters in determination of trade balance of 13 commodity groups out of 21 and customs union in 8 cases. Pattern of response of trade balance to exchange rate does not suggest a J-curve effect in any of cases. As for the long-run effect, neither exchange rate nor customs union has a statistically significant effect on trade balance of any of commodity groups, suggesting that those significant short-run effects don’t last into long-run.Ovaj rad proučava kratkoročni i dugoročni učinak tečaja i carinske unije na trgovinsku bilancu sirovina Turske s EU (15). Koristi se pristup graničnog testa gdje se u fazi odabira modela koristi nova strategija koja osigurava odabir optimalnog modela između onih koji udovoljavaju kako dijagnostici tako i kointegraciji. Rezultati ukazuju da, kratkoročno gledano, tečaj ima utjecaja na određivanje trgovinske bilance 13 grupa sirovina od 21, dok carinska unija utječe u 8 slučajeva. Uzorak odgovora trgovinske bilance na tečaj ne ukazuje na efekt J-krivulje ni u jednom slučaju. Što se tiče dugoročnog učinka, niti tečaj niti carinska unija nemaju statistički značajan učinak na trgovinsku bilancu bilo koje grupe sirovina, ukazujući na to da viđeni kratkoročni učinci ne prelaze u dugoročne

Inferencia en modelo de regresión lineal múltiple con errores de distribución secante hiperbólica generalizada

We study multiple linear regression model under non-normally distributed random error by considering the family of generalized secant hyperbolic distributions. We derive the estimators of model parameters by usingmodified maximum likelihood methodology and explore the properties of the modified maximum likelihood estimators so obtained. We show that the proposed estimators are more efficient and robust than the commonly used least square estimators. We also develop the relevant test of hypothesis procedures and compared the performance of such tests vis-a-vis the classical tests that are based upon the least square approach. Estudiamos el modelo de regresión lineal múltiple bajo errores aleatorios no distribuidos normalmente considerando la familia de distribuciones hiperbólicas secantes generalizadas. Derivamos los estimadores de los parámetros del modelo utilizando la metodología modificada de máxima verosimilitud y exploramos las propiedades de los estimadores modificados de máxima verosimilitud así obtenidos. Mostramos que los estimadores propuestos son más eficientes y robustos que los estimadores de mínimos cuadrados comúnmente utilizados. También desarrollamos la prueba relevante de los procedimientos de hipótesis y comparamos el rendimiento de tales pruebas con las pruebas clásicas que se basan en el enfoque de mínimos cuadrados.&nbsp

Firm size and job creation: evidence from Turkey

This study examines the relationship between firm size and job creation by using an extensive data set covering all non-farm Turkish businesses with 20 or more employees from 2003 to 2010. We find that small firms (firms with employees between 20 and 100 employees) have higher mean job flow rates (job creation, job destruction and net job creation rates) than large firms. Firm size and job flow rates are inversely related, and this relationship is especially prominent for firms with 50 employees or more. Although the overall pattern observed is also observed in both sectors, job creation rates in services are higher than the ones in manufacturing. The magnitudes of job destruction rates are comparable across sectors. Higher job creation rate in services but comparable job destruction rate results in higher net job creation rate in services. As for shares, only for smaller firms (20–49 and 50–99 size categories), job creation shares are greater than their shares in employment. But these firms have disproportionate job destruction shares as well. We also find that only the 20–49 category firms contribute to net job creation more than their share in employment. The smaller firms have high disproportionate shares in job creation and destruction in manufacturing and services as well

Exchange Rate and Turkish Agricultural Trade Balance with EU

This paper investigates the short-run and long-run impact of exchange rate on the trade balance of Turkish Agriculture with EU (15) countries. The bounds testing approach to the cointegration and the error correction modeling is employed. A new strategy in the model selection phase is adopted and the optimal model is selected from the set of those models that satisfy both diagnostic tests and cointegration. Thus, unlike the previous literature utilizing this approach, it is ensured that a statistically reliable and cointegrated model is picked up for estimation. Estimation results based on the data for 1988-I to 2008-IV period indicate that in the short-run real exchange rate variable affects agriculture trade balance in trade with EU(15) and depreciation of Turkish Lira improves the trade balance. As for the long-run impact of the exchange rate, depreciation of domestic currency has a statistically significant negative effect on trade balance of agriculture

Multiple linear regression model with stochastic design variables

In a simple multiple linear regression model, the design variables have traditionally been assumed to be non-stochastic. In numerous real-life situations, however, they are stochastic and non-normal. Estimators of parameters applicable to such situations are developed. It is shown that these estimators are efficient and robust. A real-life example is given.correlation coefficient, least squares, linear regression, modified maximum likelihood, multivariate distributions, non-normality, random design,

Estimation and hypothesis testing in multivariate linear regression models under non normality

This paper discusses the problem of statistical inference in multivariate linear regression models when the errors involved are non normally distributed. We consider multivariate t-distribution, a fat-tailed distribution, for the errors as alternative to normal distribution. Such non normality is commonly observed in working with many data sets, e.g., financial data that are usually having excess kurtosis. This distribution has a number of applications in many other areas of research as well. We use modified maximum likelihood estimation method that provides the estimator, called modified maximum likelihood estimator (MMLE), in closed form. These estimators are shown to be unbiased, efficient, and robust as compared to the widely used least square estimators (LSEs). Also, the tests based upon MMLEs are found to be more powerful than the similar tests based upon LSEs

Inference in Multiple Linear Regression Model with Generalized Secant Hyperbolic Distribution Errors

We study multiple linear regression model under non-normally distributed random error by considering the family of generalized secant hyperbolic distributions. We derive the estimators of model parameters by using modified maximum likelihood methodology and explore the properties of the modified maximum likelihood estimators so obtained. We show that the proposed estimators are more efficient and robust than the commonly used least square estimators. We also develop the relevant test of hypothesis procedures and compared the performance of such tests vis-a-vis the classical tests that are based upon the least square approach

Inference in multiple linear regression model with generalized secant hyperbolic distribution errors.

Estudiamos el modelo de regresión lineal múltiple bajo errores aleatorios no distribuidos normalmente considerando la familia de distribuciones hiperbólicas secantes generalizadas. Derivamos los estimadores de los parámetros del modelo utilizando la metodología modificada de máxima verosimilitud y exploramos las propiedades de los estimadores modificados de máxima verosimilitud así obtenidos. Mostramos que los estimadores propuestos son más eficientes y robustos que los estimadores de mínimos cuadrados comúnmente utilizados. También desarrollamos la prueba relevante de los procedimientos de hipótesis y comparamos el rendimiento de tales pruebas con las pruebas clásicas que se basan en el enfoque de mínimos cuadrados. We study multiple linear regression model under non-normally distributed random error by considering the family of generalized secant hyperbolic distributions. We derive the estimators of model parameters by usingmodified maximum likelihood methodology and explore the properties of the modified maximum likelihood estimators so obtained. We show that the proposed estimators are more efficient and robust than the commonly used least square estimators. We also develop the relevant test of hypothesis procedures and compared the performance of such tests vis-a-vis the classical tests that are based upon the least square approach.