How Terms of Trade Impact Economic Growth: The Case of the United States

Abstract

Abstract 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.