Henrik Sigstad is an Assistant Professor at the BI Norwegian Business School. His research focuses on legal institutions. He holds a PhD from Harvard University and an MSc from the Barcelona School of Economics.
We study what two-stage least squares (2SLS) identifies in models with multiple treatments under treatment effect heterogeneity. Two conditions are shown to be necessary and sufficient for the 2SLS to identify positively weighted sums of agent-specific effects of each treatment: average conditional monotonicity and no cross effects. Our identification analysis allows for any number of treatments, any number of continuous or discrete instruments, and the inclusion of covariates. We provide testable implications and present characterizations of choice behavior implied by our identification conditions.
Lambais, Guilherme & Sigstad, Henrik (2023)
Judicial subversion: The effects of political power on court outcomes
Are politicians in power treated more leniently in court? We show that Brazilian mayoral candidates charged with misconduct are 65 percent less likely to be convicted if they narrowly win the election. Politicians play no direct role in the judges’ careers, suggesting that formal independence does not completely insulate the judiciary from political influence. The effect is driven by districts with few judges and by judges with higher career instability.
Bhuller, Manudeep Singh & Sigstad, Henrik (2022)
Errors and monotonicity in judicial decision-making
Recent literature raises concerns about monotonicity conditions required to interpret IV estimates under heterogeneous effects. A prominent example involves random decision-maker IV designs where decision-makers exhibit systematic differences in both preferences and skills. We develop tests of monotonicity in the context of judicial decision-making using proxies of judicial errors based on appeals and reversals of trial decisions from Norwegian court records. Our tests fail to reject average monotonicity. This suggests that differences in stringencies across judges are not sufficiently driven by skills to raise concerns about the validity of the random judge IV literature.
Aaberge, Rolf; Peluso, Eugenio & Sigstad, Henrik (2019)
The dual approach for measuring multidimensional deprivation: Theory and empirical evidence
This paper is concerned with the problem of ranking and quantifying the extent of deprivation in multidimensional distributions of dichotomous deprivation variables. To this end, we introduce a family of measures of deprivation justified on the basis of dual social evaluation functions. Two alternative criteria of second-degree deprivation count distribution dominance are shown to divide the proposed family of deprivation measures into two separate subfamilies, which can be justified by a combination of correlation increasing and count neutral rearrangements. Based on EU-SILC data, we show that application of the proposed measures might lead to conclusions that differ from those attained by standard cut-off measures, and that results based on cut-off measures are more sensitive to the choice of specific measure.
Sigstad, Henrik (2021)
Judicialization of Politics: Evidence from Brazilian Local Elections
[Academic lecture]. Oslo Development Economics Workshop.
Sigstad, Henrik & Manudeep, Bhuller (2021)
Feedback and learning: The causal effects of reversals on judicial decision-making.
[Academic lecture]. Transatlantic Workshop on the Economics of Crime.