nep-law New Economics Papers
on Law and Economics
Issue of 2020‒11‒09
eight papers chosen by
Eve-Angeline Lambert, Université de Lorraine

  1. Weeding out the Dealers? The Economics of Cannabis Legalization By Emmanuelle Auriol; Alice Mesnard; Tiffanie Perrault
  2. Law incentives for juvenile recruiting by drug trafficking gangs: empirical evidence from Rio de Janeiro By Daniel Montolio; Cristiano Oliveira
  3. Complementary bidding and the collusive arrangement: Evidence from an antitrust investigation By Robert Clark; Decio Coviello; Adriano De Leverano
  4. Social Norms and Legal Design By Bruno Deffains; Claude Fluet
  5. Duration of exposure to inheritance law in India: Examining the heterogeneous effects on empowerment By Shreya Biswas; Upasak Das; Prasenjit Sarkhel
  6. Transnational machine learning with screens for flagging bid-rigging cartels By Huber, Martin; Imhof, David
  7. Corporate Debt Overhang and Credit Policy By Brunnermeier, Markus; Krishnamurthy, Arvind
  8. The public sector and privatization in Russia in 2019 By Malginov Georgiy; Radygin Alexandr

  1. By: Emmanuelle Auriol; Alice Mesnard; Tiffanie Perrault
    Abstract: We model consumer choices for cannabis in a risky environment and determine the supply of cannabis under prohibition and legalization. While introducing a legal market reduces the profits of illegal providers, it increases cannabis consumption. We show that this trade-off can be overcome by combining legalization with sanctions against users and suppliers of illegal products, and improvements to the quality of legal products. Numerical applications to the US highlight how our proposed policy mix can control the increase in cannabis consumption post-legalization and throttle the illegal market. The eviction prices we predict to drive dealers out of business are much lower than the prices of legal cannabis in the states that opted for legalization, leaving room for the black market to flourish. Analyzing the compatibility of several policy goals put forward in the public debate, including maximizing tax revenue and minimizing psychotropic consumption, we shed light on the less favorable outcomes of recent legalization reforms and suggest a new way forward.
    Keywords: cannabis, legalization, crime, policy, regulation
    JEL: I18 K32 K42 L51
    Date: 2020
  2. By: Daniel Montolio (Universitat de Barcelona & IEB); Cristiano Oliveira (Federal University of Rio Grande)
    Abstract: We evaluate the deterrence effects of the age of criminal responsibility on total drug trafficking and homicide crimes per age, based on a quasi-experiment generated by differences in punishment severity for these crimes prescribed by the Statute of the Child and Adolescent and by the Penal Code in Brazil. To this end, information from arrests conducted by the civil and military police of the state of Rio de Janeiro in 2016 and 2017 is used to estimate the local effects of treatment through a Regression Discontinuity Design. Instead of using recidivism data and/or grouping crimes with distinct punishment severity, we use as outcome variable the total number of arrests (crimes) per age for drug trafficking and homicides, which are the most common crimes related to organized crime in Rio de Janeiro. The results indicate that the increase in punishment severity generated by the Penal Code can reduce the number of drug trafficking-related crimes by 9% and homicides by 37%. Through a simple cost-benefit analysis, we suggest that increasing the punishment severity for minors who commit homicide could reduce juvenile’s engagement in a criminal career associated with gangs and generate gains in social well-being.
    Keywords: Deterrence, Quasi-Experiment, Punishment Severity, Regression Discontinuity Design
    JEL: D9 K4
    Date: 2020
  3. By: Robert Clark (Queen's University); Decio Coviello (HEC Montreal); Adriano De Leverano (ZEW - Leibniz Centre for European Economic Research in Mannheim)
    Abstract: A number of recent papers have proposed that a pattern of isolated winning bids may be associated with collusion. In contrast, others have suggested that bid clustering, especially of the two lowest bids, is indicative of collusion. In this paper, we present evidence from an actual procurement cartel uncovered during an anticollusion investigation that reconciles these two points of view and shows that both patterns arise naturally together as part of a cartel arrangement featuring complementary bidding. Using a difference-in-difference approach, we compare the extent of winning-bid isolation and clustering of bids in Montreal's asphalt industry before and after the investigation to patterns over the same time span in Quebec City, whose asphalt industry has not been the subject of collusion allegations. Our findings provide causal evidence that the collusive arrangement featured both clustering and isolation. We use information from testimony of alleged participants in the cartels to explain how these two seemingly contradictory patterns can be harmonized.
    Keywords: Auction, Bidding ring, Collusion, Complementary bidding, Clustered bids, Missing bids, Public procurement
    JEL: L22 L74 D44 H57
    Date: 2020–07
  4. By: Bruno Deffains; Claude Fluet
    Abstract: We consider legal obligations against a background of social norms, e.g., societal norms, profes-sional codes of conduct or business standards. Violations of the law trigger reputational sanctions insofar as they signal non-adherence to underlying norms, raising the issue of the design of offences. When society is only concerned with the trade-off between deterrence and enforcement costs, legal standards defining offences should align on underlying norms so long as the latter are not too deficient. When providing productive information to third parties is also a concern, legal standards should either align on underlying norms with fines that trade off deterrence against the provision of information; or legal standards should be more demanding and enforced with purely symbolic sanctions, e.g., public reprimands. Our analysis has implications for general law enforcement and regulatory policies.
    Keywords: : Stigmatization, reputational sanctions, social norms, law enforcement, legal standard, com-pliance, deterrence.
    JEL: D8 K4 Z13
    Date: 2019
  5. By: Shreya Biswas; Upasak Das; Prasenjit Sarkhel
    Abstract: Higher duration of programs that involve legal protection may entail gradual positive changes in social norms that can be leveraged by potential beneficiaries in their favor. This paper examines the heterogeneous impact of the duration of exposure to gender-neutral reforms in the inheritance law in India on two latent domains of women empowerment: intrinsic, which pertains to expansion of agency and instrumental which relates to ability to make decisions. The time lag between the year of the amendment in the respective states and the year of marriage generate exogenous variation in reform exposure across women. The findings indicate a significant non-linear increase in the instrumental as well as intrinsic empowerment. Importantly, improvements in education along with increase in the age of marriage and changes in family structure are found to be the potential channels that signal gradual relaxation of social norms and explain the higher returns to exposure on empowerment.
    Date: 2020–10
  6. By: Huber, Martin; Imhof, David
    Abstract: We investigate the transnational transferability of statistical screening methods originally developed using Swiss data for detecting bid-rigging cartels in Japan. We find that combining screens for the distribution of bids in tenders with machine learning to classify collusive vs. competitive tenders entails a correct classification rate of 88% to 93% when training and testing the method based on Japanese data from the so-called Okinawa bid-rigging cartel. As in Switzerland, bid rigging in Okinawa reduced the variance and increased the asymmetry in the distribution of bids. When pooling the data from both countries for training and testing the classification models, we still obtain correct classification rates of 82% to 88%. However, when training the models in data from one country to test their performance in the data from the other country, rates go down substantially, due to some screens for competitive Japanese tenders being similar to those for collusive Swiss tenders. Our results thus suggest that a country’s institutional context matters for the distribution of bids, such that a country-specific training of classification models is to be preferred over applying trained models across borders, even though some screens turn out to be more stable across countries than others.
    Keywords: Bid rigging; screening methods; machine learning; random forest; ensemble methods
    JEL: C21 C45 C52 D22 D40 K40
    Date: 2020–10–26
  7. By: Brunnermeier, Markus (Princeton U); Krishnamurthy, Arvind (Stanford U)
    Abstract: Many business sectors and households face an unprecedented loss of income in the current COVID recession, triggering financial distress, separations, and bankruptcy. Rather than stimulating demand, government policy's main aim should be to provide insurance to firms and workers to avoid undue scarring that will hamper a recovery, once the pandemic is past. We develop a corporate finance framework to guide interventions in credit markets to avoid such scarring. We emphasize three main results. First, policy should inject liquidity into small and medium sized firms that are liquidity constrained and for which social costs of bankruptcy are high. Second, large firms for whom solvency is the dominant issue require a more nuanced approach. Debt overhang creates a distortion leading these firms to fire workers, forgo expenditures that maintain enterprise value, and delay filing for a Chapter 11 bankruptcy longer than is socially efficient. Government resources toward reducing the legal and financial costs of bankruptcy are unambiguously beneficial. Policies that reduce funding costs are only socially desirable if the pandemic is expected to be short-lived and if bankruptcy costs are high. Last, transfers necessary to avoid bankruptcy allow borrowers to continue paying their mortgages or credit card bills and ultimately benefit owners of assets such as real estate or credit card receivables. Taxes to fund transfers should be raised from these asset owners.
    Date: 2020–06
  8. By: Malginov Georgiy (Gaidar Institute for Economic Policy); Radygin Alexandr (Gaidar Institute for Economic Policy)
    Abstract: From 2016, statistical data began to be published in the framework of the System of Public Property Management Efficiency Estimates (hereinafter – System of Estimates). It was approved by Decree of the RF Government No 72 dated January 29, 2015, to replace the public sector monitoring data, collected and released by the Federal State Statistics Service (Rosstat) since the early 2000s in accordance with RF Government Decree No 1 dated January 4, 1999 (as amended on December 30, 2002). The System of Estimates contains data on the number of federal state unitary enterprises (FSUEs) and joint-stock companies (JSCs) with RF stakes in their capital, which had been previously published, as a rule, in the government privatization programs for the next period (from 2011 – for three-year period, and prior to 2011 – for one-year period). Such data can also be found in the newly adopted forecast plan (program) of federal property privatization (FPP), as well as in the Main Directions of Federal Property Privatization for 2020–2022 approved by RF Government Directive No 3260-r dated December 31, 2019.
    Keywords: Russian economy, public sector, privatization
    JEL: K11 H82 L32 L33
    Date: 2020

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