What Determines Migration Flows From Low‐income to High‐income Countries? An Empirical Investigation of FIJI–U.S. Migration 1972–2001

Abstract

This article examines the long‐run and short‐run determinants of migration from Fiji to the United States between 1972 and 2001 using a human capital framework, which is extended to take account of political instability in Fiji. In the long‐run the authors find that differences in income levels, disparities in police strength, disparities in the number of doctors, costs of moving, and political instability in Fiji are all statistically significant with the expected sign. In the short run the cost of moving, lagged migration, political instability, and differences in both police strength and medical care are the main determinants of Fiji–United States immigration. (JEL C22, F22)

Does export product quality matter for CO2 emissions? Evidence from China

“…The coefficient of the lagged error correction term (ECTt-1) is −1.616, and it is found to be statistically significant at the 1% level. Following, Narayan and Smyth (2006), and Gozgor and Can (2016a), the negative sign and elastic coefficient mean that CO2 emissions in China gradually converge to its long-run equilibrium path by a speed of adjustment through the channels of the real GDP per capita, squared real GDP per capita, energy consumption per capita, and export quality. In addition, the results of the long-run Granger causality / VECM tests are provided in Table 5.…”

A Survey on the Factors Affecting Current Account Balance of Turkey: Evidence From Ardl-Bounds Testing Approach

“…If the value of the lagged error correction terms coefficient is between -1 and -2, this shows the lagged error correction term produces dampened fluctuations in current account balance about the equilibrium path. As seen from the results of the short-run model, coefficient of the lagged error correction term is found to be -1.02, which implies that instead of monotonically converging to the equilibrium path directly, the error correction process fluctuates around the long-run value in a dampening manner and when this process is completed, convergence to the equilibrium path is expected to be rapid (Narayan and Smyth, 2006).On the other hand results of the short run analysis reveal that the current account balance of Turkey is affected mostly from the lagged value of itself, from foreign trade balance and also from the lagged value of real effective exchange rate.…”

“…To apply the bounds testing approach, firstly an unrestricted error correction model is formed. Narayan and Smyth (2006) notes that the ARDL approach is expected to have better statistical properties than the Engle and Granger (1987) and Johansen and Juselius (1990) methods because it draws on the unrestricted error correction model. The bounds test procedure for checking the cointegration relationship between the variables in Equation (1) is conducted with the following ARDL model: http://www.iises.net/proceedings/22nd-international-academic-conference-lisbon/front-page…”

A Survey on the Factors Affecting Current Account Balance of Turkey: Evidence From Ardl-Bounds Testing Approach

“…If the value of the lagged error correction terms coefficient is between -1 and -2, this shows the lagged error correction term produces dampened fluctuations in current account balance about the equilibrium path. As seen from the results of the short-run model, coefficient of the lagged error correction term is found to be -1.02, which implies that instead of monotonically converging to the equilibrium path directly, the error correction process fluctuates around the long-run value in a dampening manner and when this process is completed, convergence to the equilibrium path is expected to be rapid (Narayan and Smyth, 2006). According to the results, the lagged dependent variable is statistically significant with a positive coefficient.…”

“…To apply the bounds testing approach, firstly an unrestricted error correction model is formed. Narayan and Smyth (2006) notes that the ARDL approach is expected to have better statistical properties than the Engle and Granger (1987) and Johansen and Juselius (1990) methods because it draws on the unrestricted error correction model. The bounds test procedure for checking the cointegration relationship between the variables in Equation (1) is conducted with the following ARDL model:…”