“…We examine whether and how analyst capex forecasts affect investment efficiency by estimating the following panel regression separately for the under‐ and overinvestment subsamples: where INVEST _ INEFF i , t captures investment (in)efficiency, which is the absolute value of the residuals from estimating the investment model as described in the section “Investment efficiency.” 8 N _ CPXAF i , t is the natural logarithm of the number of analyst capex forecasts issued over the three‐month period extending through the first quarter of the forecast target year. CONTROL i , t −1 represents a vector of variables that control for (i) various firm characteristics previously found to affect investment efficiency (Bae et al 2018; Biddle et al 2009; Chen et al 2013), namely, the issuance of capex guidance ( CPXGD ), which is an indicator variable that equals one if a firm issues management capex forecasts over the same horizon as that over which N_CPXAF is calculated, the existence of analyst earnings forecasts ( EPSAF ), financial reporting quality ( FRQ ), which is measured as accruals quality based on the modified Dechow and Dichev (2002) model; (ii) basic firm characteristics, including market‐to‐book ratio ( M/B ), firm age ( AGE ), institutional ownership ( IO ), firm's operating cycle ( OPCYCLE ), asset tangibility ( TANGIBILITY ), bankruptcy risk ( Z_SCORE ), cash flow from operations divided by sales ( CFOSALE ), whether the firm has reported negative earnings ( LOSS ), leverage ( LEV ) and financial slack ( SLACK ); and (iii) uncertainty of firms' operating environment, including cash flow volatility ( CFOVOL ), sales volatility ( SALESVOL ), and investment volatility ( INVESTVOL ). Detailed variable definitions are provided in the Appendix.…”