Does poor legal enforcement make households credit-constrained?

Fabbri, Daniela; Padula, Mario

doi:10.1016/j.jbankfin.2003.09.009

“…On a related note, Fabbri and Padula (2003) document that in Italian provinces with a higher backlog of judicial cases, higher wealth households borrow relatively larger amounts. Gropp et al (1997) compare US states with different bankruptcy exemption levels and document that greater exemptions imply that households in the bottom quartiles of the wealth distribution borrow relatively lower amounts of debt -conditional on borrowing.…”

Section: Economic Magnitude Of the Responsesmentioning

confidence: 97%

“…Regarding the amount of secured debt held, the impacts of time to repossess vary substantially across cohort/age groups.Conditional on obtaining a secured loan, a 15 months longer repossession period decreases by 12 per cent the amount of debt held by the set of households aged [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] and with characteristics other than age held at those of the reference group. 41 .…”

Section: Economic Magnitude Of the Responsesmentioning

confidence: 99%

The Distribution of Debt Across Euro Area Countries: The Role of Individual Characteristics, Institutions and Credit Conditions

Bover

¹

,

Casado

²

,

Costa

³

et al. 2013

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The HFCN collects household-level data on households' finances and consumption in the euro area through a harmonised survey. The HFCN aims at studying in depth the micro-level structural information on euro area households' assets and liabilities. The objectives of the network are: Terms of use: Documents in EconStor may1) understanding economic behaviour of individual households, developments in aggregate variables and the interactions between the two;2) evaluating the impact of shocks, policies and institutional changes on household portfolios and other variables;3) understanding the implications of heterogeneity for aggregate variables; 4) estimating choices of different households and their reaction to economic shocks; 5) building and calibrating realistic economic models incorporating heterogeneous agents; 6) gaining insights into issues such as monetary policy transmission and financial stability.The refereeing process of this paper has been co-ordinated by a team composed of Gabriel Fagan (ECB), Pirmin Fessler (Oesterreichische Nationalbank), Michalis Haliassos (Goethe University Frankfurt) , Tullio Jappelli (University of Naples Federico II), Sébastien PérezDuarte (ECB), Jiri Slacalek (ECB), Federica Teppa (De Nederlandsche Bank), Peter Tufano (Oxford University) and Philip Vermeulen (ECB).The paper is released in order to make the results of HFCN research generally available, in preliminary form, to encourage comments and suggestions prior to final publication. The views expressed in the paper are the author's own and do not necessarily reflect those of the ESCB. AcknowledgementsThe views expressed in this paper are those of the authors and do not necessarily reflect those of the respective National Central Banks or the European Central Bank. We would like to thank Asa Johansson for providing data on pre-and after-tax mortgage interest rates and Richard Blundell and an anonymous referee for helpful comments. All remaining errors are our own. Olympia Bover (corresponding author)Banco de España; e-mail: bover@bde.es Banco de EspañaOlympia Bover, Jose Maria Casado and Ernesto Villanueva Banco de Portugal Sonia Costa National Bank of Belgium Philip Du Caju Central Bank of Ireland Yvonne McCarthy CEPS / INSTEAD Research Institute Eva Sierminska Bank of Greece and Deutsche Bundesbank Panagiota Tzamourani National Bank of Slovakia Tibor ZavadilAbstract The aim of this paper is twofold. First, we present an up-to-date assessment of the differences across...

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“…The first chart on the top row of Figure 3 reports the results for the reference group. 19 Web appendix is available at https://www.dropbox.com/s/wie95bwb1pi90vb/web_appendix.pdf Across all countries, the amount of secured debt holdings is highest for households where the reference person is aged 16 to 34 years. In almost all cases, households with heads older than 45 years tend to hold lower amounts of debt relative to the omitted group, 35 to 44 year olds.…”

Section: The Amount Of Debt Heldmentioning

confidence: 99%

The Distribution of Debt Across Euro Area Countries: The Role of Individual Characteristics, Institutions and Credit Conditions

Bover

¹

,

Casado

²

,

Costa

³

et al. 2013

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The HFCN collects household-level data on households' finances and consumption in the euro area through a harmonised survey. The HFCN aims at studying in depth the micro-level structural information on euro area households' assets and liabilities. The objectives of the network are: Terms of use: Documents in EconStor may1) understanding economic behaviour of individual households, developments in aggregate variables and the interactions between the two;2) evaluating the impact of shocks, policies and institutional changes on household portfolios and other variables;3) understanding the implications of heterogeneity for aggregate variables; 4) estimating choices of different households and their reaction to economic shocks; 5) building and calibrating realistic economic models incorporating heterogeneous agents; 6) gaining insights into issues such as monetary policy transmission and financial stability.The refereeing process of this paper has been co-ordinated by a team composed of Gabriel Fagan (ECB), Pirmin Fessler (Oesterreichische Nationalbank), Michalis Haliassos (Goethe University Frankfurt) , Tullio Jappelli (University of Naples Federico II), Sébastien PérezDuarte (ECB), Jiri Slacalek (ECB), Federica Teppa (De Nederlandsche Bank), Peter Tufano (Oxford University) and Philip Vermeulen (ECB).The paper is released in order to make the results of HFCN research generally available, in preliminary form, to encourage comments and suggestions prior to final publication. The views expressed in the paper are the author's own and do not necessarily reflect those of the ESCB. AcknowledgementsThe views expressed in this paper are those of the authors and do not necessarily reflect those of the respective National Central Banks or the European Central Bank. We would like to thank Asa Johansson for providing data on pre-and after-tax mortgage interest rates and Richard Blundell and an anonymous referee for helpful comments. All remaining errors are our own. Olympia Bover (corresponding author)Banco de España; e-mail: bover@bde.es Banco de EspañaOlympia Bover, Jose Maria Casado and Ernesto Villanueva Banco de Portugal Sonia Costa National Bank of Belgium Philip Du Caju Central Bank of Ireland Yvonne McCarthy CEPS / INSTEAD Research Institute Eva Sierminska Bank of Greece and Deutsche Bundesbank Panagiota Tzamourani National Bank of Slovakia Tibor ZavadilAbstract The aim of this paper is twofold. First, we present an up-to-date assessment of the differences across...

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“…Enforcement According to the theoretical model of Fabbri and Padula (2004), households are less likely to be credit constrained when loan contracts are enforced more strongly because households' incentive to repay increases. In this section, we test whether better judicial enforcement decreases the probability of being rationed using both a pooling logit model and a random effects logit model.…”

Section: A the Probability Of Being Credit Constrained And The Degrementioning

confidence: 99%

“…While many previous studies have used the number of pending trials as an indicator of poor judicial enforcement, they have used different normalization measures such as population, the number of judges, and the number of court personnel. In our analysis, we normalized the number of pending trials by the number of incoming trials, as done by Fabbri and Padula (2004), but the estimation results do not change even if we use different normalization measures such as population and the number of judges. As in the case of the first indicator of the degree of judicial enforcement, we used three dummy variables for the second indicator--namely, 1 st Enforcement Quartile2, 2 nd Enforcement Quartile2, and 3 rd Enforcement Quartile2, with the highest quartile (45.5 or higher) being the excluded category.…”

mentioning

confidence: 99%

The Degree of Judicial Enforcement and Credit Markets: Evidence from Japanese Household Panel Data

Horioka

¹

,

Sekita

²

2009

SSRN Journal

0

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractIn this paper, we conduct an empirical analysis of the impact of better judicial enforcement on the probability of being credit rationed, loan size, and the probability of bankruptcy using household-level data from the Japanese Panel Survey of Consumers, conducted by the Institute for Research on Household Economics, in conjunction with judicial data by court district on trial length and the ratio of the number of pending civil trials to the number of incoming civil trials. Contrary to the predictions of the existing theory, we find that better judicial enforcement increases the probability of being credit rationed and decreases loan size. Furthermore, we find that better judicial enforcement increases the probability of bankruptcy, a result that is consistent with lax screening effects.Keywords: Judicial enforcement; Credit allocation; Credit rationing; Bankruptcy; Screening; Household Behavior; Borrowing JEL classification numbers: D12; G21; G33; K12; K41; K42 2 Since the mid-1990s, the impact of legal systems on the economy has been the focus of many theoretical and empirical investigations. As one example of this, many studies, which originate with La Porta, Lopez-De-Silanes, Shleifer, and Vishny (1997), have analyzed the relationship between legal systems and financial markets. In these studies, the following two channels through which the legal system affects financial markets were identified: (1) the degree of judicial enforcement and (2) the content of the law.In Japan, since laws apply to the nation as a whole, the content of the law is uniform in all judicial districts. However, the degree of judicial enforcement may vary from district to district. Thus, this paper focuses on differences in the degree of judicial enforcement from district to district. The fact that the content of the law is uniform throughout the country in Japan makes it possible to distinguish the impact of the degree of enforcement from that of the content of the law, whereas this is not possible in other countries, where different states have different laws.The length of trials in Japan has become shorter and shorter over time. For example, the average length of civil trial proceedings in district courts was 17.3 months in 1973, 12.9 months in 1990, and 7.8 months in 2006. In 2003, the "Act on the Expedition of Trials" 1 was promulgated with the objective of concluding trials as quickly as possible and protecting defendants' r...

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Does poor legal enforcement make households credit-constrained?

Cited by 103 publications

References 11 publications

The Distribution of Debt Across Euro Area Countries: The Role of Individual Characteristics, Institutions and Credit Conditions

The Distribution of Debt Across Euro Area Countries: The Role of Individual Characteristics, Institutions and Credit Conditions

The Distribution of Debt Across Euro Area Countries: The Role of Individual Characteristics, Institutions and Credit Conditions

The Degree of Judicial Enforcement and Credit Markets: Evidence from Japanese Household Panel Data

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