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This study by Bogaard and Svejnar delves into the HR management effects in the branches of a Canadian bank, focusing on incentives, participation, and skills of branch managers. It explores the impact of HRM on sales annual percentage change by considering various factors like branch age, manager tenure, and market characteristics. The research utilizes innovative empirical strategies, including unit fixed effects and time-varying instrumental variables, to analyze the adoption of High-Performance Work Practices (HPWP) and its implications on productivity, wages, and job satisfaction. It also investigates the differences in treatment between bankers and advisors and the effects of regional and size variations in adoption. The study highlights the importance of robustness checks and explores the potential challenges and implications of late adoption in HRM practices.
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Incentives in a (Czech?) Bank by Bogaard and Svejnar
HRM effects in services • Ann Bartel 2004 ILLR (100 citations in GS) Branches of a Canadian bank, branch manager decides on HRM (incentives, participation, skills), 2 periods, controls for manager quality using employee survey: sales annual % change= f(K, L, HRM, branch_age, MgrTenure, MarketX, FE_year, FE_branch, FE_mgr ) • Ichniowski&Shaw: insider econometrics: is the goal to measure adoption effect in a randomly chosen branch or early adopters?
Literature • Evidence on HPWP: makes productivity go up as well as wages and job satisfaction, profits don't change much, more likely to be adopted when skilled labor is abundant. • Strategies: unit FE, time varying IV using industry adoption of HPWP from another country, matching.
Bogaard and Svejnar This is not HPWP, but basic specialization. (+) Nice new data, alternative empirical strategies (IV, matching), lots of robustness checks, model to aid interpretation. 56 pages (and I’ll ask for 10 more). Wow. (-) Whole lotta IVing going on, head swimming. Stress on foreign/domestic in CEE in 2003-07? Magnitude of IV estimates huge (2x s.d.?).
Experiment Region and size explain adoption. Bankers and advisors a different treatment. Need more info on the design (var in X): • Was this a surprise? Not much pre- data. • Who chose order of implementation? (within size or regional groups) In particular, early adoption (in t=1) as pilot in best branches, low hanging fruit within & across branches?
IV strategy • IV idea: Regional/size adoption. Sequencing? • Then add size to both first and second stage? • IV is not similar to matching: IV is an across- group comparison (averaging unobs. within groups) zooming in on late adopters (LATE), whilst matching compares within groups. • Show missing 500 obs., first stage F tests, pscore estimation, common support, balancing tests, dif-in-difs w/ matching implementation (within group pscore?) etc.
Minor Questions • Free riding or lower returns to late adopters? • Care about side payments? • Take out advisors in small branches in 2006? • Can do better on local demand? Un. rates? • No info on new footing (flow)? • Study effect on wages? • Must look at bad loans over time.