ABSTRACT
Studiul s-a concentrat pe determinarea politicilor guvernamentale esenţiale si a barierelor comerciale care afectează performanţa exporturilor industriei textile în timpul pandemiei de COVID-19. Acest studiu a analizat influenţa politicilor guvernamentale de export asupra performanţei la export a industriei textile. Acest studiu a comparat, de asemenea, factori din trei industrii textile din Asia de Sud, respectiv Pakistan, India si Bangladesh. Studiul a identificat nouă politici guvernamentale de export esenţiale si bariere comerciale bazate pe vizualizarea organizaţiei industriale (Vizualizarea I/O). A fost utilizat un model de regresie de tip panel pentru a analiza semnificaţia fiecărei politici guvernamentale si barierele comerciale care afectează performanţa exporturilor de produse textile. Rezultatele studiului au arătat că ratele de schimb valutar, costul de export, timpul de export, stabilitatea politică a ţării, calitatea infrastructurii din ţară, libertatea din corupţie, costul de afaceri al terorismului si stabilitatea economică în ţară au un efect semnificativ asupra performanţei la export a industriei. În schimb, taxele pentru desfăşurarea afacerilor au un efect nesemnificativ asupra performanţei la export. Testul de Estimare aparent fără legătură (SUEST) a comparat diferenţele de performanţă la export ale industriilor textile din Pakistan, India si Bangladesh datorate politicilor guvernamentale. Rezultatele au arătat că un nivel mai ridicat de timp pentru export, costul de export si costul pentru desfăsurarea afacerilor terorismului duc la performanţa scăzută la export a industriei textile. În acelasi timp, un nivel mai ridicat al cursurilor de schimb valutar, stabilitatea politică a ţării, calitatea infrastructurii, libertatea din corupţie si stabilitatea economică în ţară duc la performanţe ridicate la export ale industriei textile. Mai mult, taxele pentru desfăsurarea afacerilor au un efect nesemnificativ asupra performanţei la export. Acest studiu este printre puţinele care abordează industria textilă în timpul pandemiei de COVID-19. Din cauza circumstanţelor incerte, va fi greu pentru guvern să identifice factori importanţi care ar putea ajuta exportatorii de textile să supravieţuiască si să se dezvolte în timpul pandemiei de COVID-19. Studiul a identificat politici guvernamentale importante si bariere comerciale care afectează exporturile de textile pe baza unui sprijin teoretic solid si a comparat si a elaborat, de asemenea, importanţa fiecărui factor în trei ţări din Asia de Sud. Acest studiu va ajuta factorii de decizie să-si reconsidere factorii legaţi de export pentru a-si spori exporturile de textile si pentru a-si relansa economia după pandemia de COVID-19.Alternate :The study focused on determining essential government policies and trade barriers affecting the textile industry's export performance during the COVID-19 pandemic. This study has analysed the effect of government export policies on the export performance of the textile industry. This study has also compared factors among three South Asian textile industries, including Pakistan, India, and Bangladesh. The study identified nine essential government export policies and trade barriers based on Industrial Organization View (I/O View). A panel regression model was used to analyse the significance of each government policy and trade barrier affecting textile export performance. Results of the study showed that currency exchange rates, the cost to export, time to export, political stability of the country, quality of infrastructure in the country, freedom from corruption, business cost of terrorism and economic stability in the country have a significant effect on export performance of the industry. In contrast, taxes on doing business have an insignificant effect on export performance. The Seemingly Unrelated Estimation (SUEST) test compared the differences in export performance of Pakistani, Indian and Bangladeshi textile industries due to governmen policies. The results showed that a higher level of time to export, cost to export and business cost of terrorism lead to the low export performance of the textile industry. At the same time, a higher level of currency exchange rates, political stability of the country, quality of infrastructure, freedom from corruption and economic stability in-country lead to the high export performance of the textile industry. Further, taxes on doing business have an insignificant effect on export performance. This study is among the few contributing to the textile industry during the COVID-19 pandemic. Due to uncertain circumstances, it becomes hard for the government to identify important factors which could help textile exporters to survive and grow during the COVID-19 pandemic. The study has identified important government policies and trade barriers affecting textile exports based on strong theoretical support and has also compared and elaborated on the importance of each factor across three South Asian countries. This study will help policymakers reconsider exportrelated factors to enhance their textile exports and revive their economy after the COVID-19 pandemic.
ABSTRACT
Exchange rates are crucial in regulating the foreign exchange market's dynamics. Because of the unpredictability and volatility of currency rates, the exchange rate prediction has become one of the most challenging applications of financial time series forecasting. This study aims to build and compare the accuracy of various methods. The time series model Auto-Regressive Integrated Moving Average (ARIMA) and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) are utilized to forecast the daily US dollar to Pakistan rupee currency exchange rates (USD/PKR). Lagged observations of the data series and moving average technical analysis are used in both models. Explanatory factors were used as indicators, and the prediction performance was assessed using a variety of commonly known statistical metrics. These statistical metrics suggested the presence of conditional heteroscedasticity. Thus, the process turns to capture the volatility effect of conditional heteroscedasticity through GARCH modeling. It may be inferred based on the results of tentative models;that the ARCH model outperforms the GARCH model in terms of predicting the USD/PKR exchange rate.