This study employed Vector Error Correction Model (VECM) and Granger causality tests to analyze the relationships among macroeconomic variables—Gross Domestic Product (GDP), Gasoline Price (GAS), House Price Index (HPI), M2 Money Supply (M2)—management variables, including the Total Number of Electric Vehicle Charging Locations (EVCL) and Tesla Sales (SALES), and Tesla's stock price (TSLA). Utilizing a dataset comprising 105 monthly observations from July 2015 to March 2024, the Granger causality results indicate positive associations of GDP, M2, HPI, and Tesla Sales with Tesla's stock price, while Gasoline Price shows no significant effect. Additionally, GDP and M2 positively influence Tesla sales, and significant interactions are found between GDP and M2, M2 and HPI, and EVCL and GDP. The cointegration test results confirm long-run equilibriums where Tesla’s stock price and sales are positively associated with GDP and M2, but negatively with Gasoline Price and HPI. EVCL shows a positive relationship with GDP, HPI, and M2, and a negative relationship with Gasoline Price. Short-run dynamics also reveal significant interactive effects among the seven variables. These findings provide crucial insights between macroeconomic and management variables and Tesla’s stock price, offering valuable information for policymakers and investors.
목차
Abstract 1. Introduction 2. Literature Review 2.1 Variables on Electric Vehicles 2.2 Macroeconomic variables on stock market 3. Data and Methodology 3.1 Analytical Procedure 3.2 Description of Variables 4. Empirical results 4.1 Unit root test 4.2 Causality test 4.3 Cointegration test 5. Long-run and Short-run equilibrium 5.1 Long-run equilibrium 5.2 Short-run equilibrium 6. Impulse response analysis and variance decomposition analysis 6.1 Impulse response analysis 6.2 Variance decomposition analysis 7. Discussion and Conclusion 8. Limitation References
키워드
MacroeconomicsTesla Stock PriceTesla SalesVector Error Correction Model (VECM)