Investigating the crowding effect of FDI on domestic investments: Evidence from Bangladesh.

This study empirically investigates the crowding effect of Foreign Direct Investment (FDI) on domestic investments in Bangladesh, utilizing annual time series data from 1972 to 2022. Initially, unit root tests are conducted with and without considering structural breaks in the dataset. This study employs the Johansen test of cointegration to investigate the enduring association between the variables and utilizes the Vector Error Correction Model (VECM) to accommodate this relationship over the long term. Following the estimation of the VECM, formulas about the magnitude of the crowding effect (CE) are applied to examine the impact of FDI on domestic investment in Bangladesh. Results indicate that FDI positively influences domestic investments in both the short and long run.

Exploring the nexus between FDI inflows and economic growth: A sectoral level analysis.

This study investigates the relationship between Foreign Direct Investment (FDI) inflows and economic growth at sectoral levels in Bangladesh, employing a panel study framework. Utilizing sectoral-level panel data spanning six sectors from 2007-08 to 2018-19, the analysis is conducted using Panel Vector Error Correction Model (Panel VECM). Results from panel unit root tests confirm that all variables are integrated of order one I (1), indicating stationarity. The Pedroni panel co-integration test further supports the presence of co-integration among the variables. Notably, the Panel VECM reveals evidence of a unidirectional causal relationship from Real Gross Domestic Product (RGDP) to Real Foreign Direct Investment (RFDI) across all six sectors of Bangladesh. The findings underscore the significance of formulating pragmatic policies and implementing them effectively to attract FDI across sectors, thereby contributing to the overall economic growth of Bangladesh.

Relationship between greenfield investment and economic growth: Evidence from Bangladesh.

The key purpose of the study is to investigate the relationship between Greenfield investment and economic growth of Bangladesh using annual time series data during the period 2003-2020. The study employs Toda-Yamamoto (T-Y) tests of Granger causality method that performs Modified Wald Test (MWALD) in order to establish causal relation among different variables. There are three steps in implementing the T-Y procedure. The first step involves using different tests (ADF, PP, and KPSS test) to identify the maximum order of integration of the variable. The second step requires selecting the optimal lag length (p) based on several lag length selection criteria. In the third step, MWALD approach is used for testing the vector auto regression model for causality. The results of the tests (ADF, PP, and KPSS) concluded that the maximum order of integration of the variables is two. Then, the optimal lag length of two (p = 2) has been selected based on several lag length selection criteria. Finally, the findings reveal the evidence of unidirectional causality from Real Greenfield Foreign Direct Investment (RGFDI) to Real Gross Domestic Product (RGDP). The key contribution of this study is to investigate the Greenfield investments-growth relationship for a country like Bangladesh.