Trade has a crucial role in a country’s economic development. This study scrutinizes the impact of terms of trade (TOT), labor force, and capital on the United States’ economic growth. This study aims to investigate the short and long-run impacts of Capital, Labor, and Terms of Trade on the economic growth of the United States. To accomplish the study’s goals, this study analyzed a time series of annual data for the United States from 1980 to 2021. The Philipps-Perron test, the model of Augmented Dickey-Fuller (ADF) model, and the Autoregressive Distributed lag (ARDL) of the bound tests were applied to test whether the data is stationary or not. We employed an Autoregressive Distributed lag (ARDL) unit root model to examine the study variables’ short- and long-term associations. The outcomes of the unit root of the (ADF) test explain that both the Trace and Maximum Eigenvalues values showed that the study’s variables were stationary at both level and first difference, but stationarity was not there at the first difference using the PP model. At I(0) and I(1), the log(GDP), labor, capital, and log(TOT) stayed stationary. However, the estimated results of the (ARDL) model revealed that the economic growth of the United States was negatively and significantly affected by the (TOT), but economic growth, capital, and the labor force have favorable long and short-run relationships. The results of ECM(-1) imply that 7% of adjustment from disequilibrium to equilibrium from short-run to long-run. This study’s findings suggest that policymakers and governments ease trade between countries to achieve the highest economic growth.
Purpose – Trade is influenced highly by the economic development of a country. This study scrutinizes the impact of the Terms of Trade (TOT), the force of labor, and capital on the United States’ economic growth. In addition, the study also sets an objective to investigate the short-run as well as the long-run impact of Capital, Labor, and Terms of Trade on the economic growth of the United State. Methodology/Design/Approach – To accomplish the study's goals, this study analyzed the time series of annual data for the United States for the period of 1980 to 2021. The Philipps-Perron tests, the model of Augmented Dickey-Fuller (ADF), and the Autoregressive Distributed lag (ARDL) of a bound test were applied to test, is the data stationary or not. We employed the Autoregressive Distributed lag (ARDL) unit root model to examine the short- and long-term associations between the study variables. Findings – The outcomes of the unit root of the (ADF) test explain that both the Trace and Maximum Eigenvalues values showed that the study’s variables were discovered stationary at both level and first difference, but the stationarity was not there at the first difference using the PP model. At I(0) and I(1), the log(GDP), labor, capital, and the log(TOT) stayed stationary. However, the estimated results of the (ARDL) model revealed that the economic growth of the United States was negatively and significantly affected by the (TOT), but economic growth, capital, and the labor force have a favorable long-term and short-term relationship. Practical implications – This study suggests policymakers and governments ease trade between countries to achieve the highest economic growth. Originality/value – By evaluating recent and latest time series, annual data by three models to scrutinize the term of trade, capital, and labor force impact on the United States' economic growth. Hence, this study tried to fill this gap in the literature by providing policy recommendations.
The study aim is to investigate the Industrial, Agricultural, and Technological Bilateral Trade relationship between China and the Europe & Central Asia region over the period of 2000 to 2019 by employing the Revealed Comparative Advantage Index (RCA export), Trade Complementarity Index (TCI) and Trade Integration Index (TCD). The estimated results showed that there is a strong Bilateral Trade relationship between China and Europe & Central Asia. The estimated results of the Trade Complementarity Index (TCI) indicates that between 20 industries' product 17 have strong TCI between China and Europe, which showed that the export and import between China and Europe & Central Asia are matched, only three of the industries product, which are vegetable, Fuels, and Minerals are not matched strongly, the Trade Integration Index (TCD) between China and Europe from 2000 to 2019 is less than 1 that explains the Trade Integration Index between China and Europe are weak which give us knowledge that Chinese trade didn’t depend strongly on the Europe & Central Asia, estimated results of the Revealed Comparative Advantage Index (RCA export) between China and Europe examine that there have strong the Revealed Comparative Advantage between China and Europe of all 20 different industries product.
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