Re‐estimating the effect of heterogeneous standards on trade: Endogeneity matters

Abstract

Controlling for endogeneity‐induced biases and accounting for the source of heterogeneity may both matter for the proper empirical estimation of the effect of heterogeneous standards on trade. However, existing literature on the trade effects of heterogeneity in pesticides maximum residue levels (MRLs) does not directly address the problem of endogeneity in the standards–trade relationship. Using pesticides MRL data for 53 countries over 2005–14, we thus re‐examine the trade effects of stricter (than partner) standards accounting for endogeneity using panel data methods. We find that the direction of the estimated trade effects gets reversed, thereby underlining the greater demand‐enhancing effect of more stringent regulation. We also discuss why endogeneity may bias the estimates downwards. In another original contribution, we examine the standards–trade relationship by the direction of imposition of stricter standards for a large panel. Our results suggest that stricter standards do not impede trade, irrespective of who imposes them.

Enhance or inhibit? Unveiling the influence of chairman’s hometown attachment on the corporate philanthropy–Corporate financial performance relationship

“…According to Shingal et al (2021) and relevant studies, there are five leading causes for the endogeneity problem in management research: selection bias, variable measurement error, reverse causality, omitted variable bias, and dynamic panel deviation. In different studies, the endogeneity problems vary.…”

Does the internationalisation of China's agri‐food standards affect export quality upgrading?—Evidence from firm‐product‐level data

“…In Equation (), we use destination‐year fixed effects () to account for multilateral resistance in line with Xiong and Beghin (2012) as occurring frequently. Second, we also use the Poisson‐pseudo‐maximum likelihood (PPML) estimator to test the standards on trade flows to avoid the effect of zero trade value in explained variables (Shingal et al, 2020). Third, to control for heteroskedasticity, we compute robust standard errors clustered at the firm level to address the potential correlation of error terms within each firm across different products over time (Fan et al, 2015).…”

Catalyst or barrier? Heterogeneous effects of standards on agricultural trade between China and the Belt and Road countries

“…In the regression of the baseline model, the number of standards with one lag period is used. Some scholars (Blind, 2004; Mangelsdorf, 2011) believe that the formulation of standards is a complex process requiring significant participation of relevant stakeholders, but others doubt that an increase in trade volume will influence standard‐setting (Berti & Falvey, 2018; Shingal et al, 2021). A time lag also may exist between the formulation and implementation of national standards.…”