Dynamic Determinants of Share Price in Emerging Markets: Evidence from System GMM Estimation in Nigeria - Edokpa, Solomon Ighodalo; Akpadaka, Ovbe Simon (Quantitative Economics and Management Studies, 2025)
This study investigates the dynamic determinants of share price among listed firms in Nigeria’s Consumer Goods and Agriculture sectors using a decade-long panel dataset covering the period from 2012 to 2023. Anchored on the theoretical perspectives of the Efficient Market Hypothesis, Signalling Theory, and Agency Theory, the study evaluates how firm-specific indicators such as earnings per share (EPS), return on equity (ROE), current ratio, debt-to-equity ratio, and total asset turnover, as well as macroeconomic variables like exchange rate and GDP per capita, influence share price in an environment characterised by institutional inefficiencies and information asymmetry. The empirical analysis begins with a static panel regression using the Fixed Effects model to establish a baseline understanding. To improve robustness and account for econometric challenges such as endogeneity, serial correlation, and unobserved heterogeneity, the study adopts the two-step System Generalised Method of Moments (System GMM) as the main estimation technique. The dynamic model reveals strong persistence in share price, as lagged share price is significantly associated with current values. While EPS shows a positive and significant effect in the static model, the dynamic GMM results indicate a negative and significant relationship, suggesting that reported earnings may reflect investor scepticism or earnings manipulation, particularly in contexts with weak governance oversight. Other variables, including ROE, leverage, and macroeconomic indicators, remain statistically insignificant in the dynamic specification. Year effects are incorporated to control for time-specific macro shocks. This study contributes to frontier market finance literature by offering sector-specific insights and demonstrating the added value of dynamic modelling. It also cautions investors and policymakers against excessive reliance on earnings-based metrics without adequate consideration of the institutional environment.