Josef Montag

Bio: Josef Montag is an academic researcher from Charles University in Prague. The author has contributed to research in topics: Unemployment & Punishment. The author has an hindex of 8, co-authored 32 publications receiving 203 citations. Previous affiliations of Josef Montag include Academy of Sciences of the Czech Republic & University of Economics, Prague.

Does homeownership hinder labor market activity? Evidence from housing privatization and restitution in Brno

Abstract: We study the effects of homeownership on labor force participation and unemployment. We exploit housing privatization and restitution after the fall of communism as a source exogenous assignment of homeowner/renter status, using a unique dataset from the city of Brno, Czech Republic. We do not find any evidence of homeownership hindering labor force participation. In fact, our estimates suggest that homeownership reduces unemployment by four to six percentage points. Homeownership appears to decrease the risk of unemployment by about one third to one half, relative to renters. The estimated effects on labor force participation are systematically around zero.

A Radical Change in Traffic Law: Effects on Fatalities in the Czech Republic

Abstract: I evaluate the effects of a new road traffic law in the Czech Republic that became effective on July 1, 2006. The law introduced tougher punishments through the introduction of a demerit point system and a manifold increase in fines, together with an augmented authority of traffic police. I find a sharp, 33.3 percent, decrease in accident-related fatalities during the first three post-reform months. This translates into 51 to 204 saved lives with 95 percent certainty. The decline was, however, temporary; estimates of the effects going beyond the first year are around zero. Unique data on traffic police activity reveal that police resources devoted to traffic law enforcement gradually declined and were shifted towards general law enforcement.

A radical change in traffic law: effects on fatalities in the Czech Republic

Abstract: BACKGROUND: This study examines short- and long-run effects of a new-stricter-road traffic law on traffic accident-related fatalities in the Czech Republic. The law introduced tougher punishments through the introduction of a demerit point system and a manifold increase in fines, together with augmented authority of traffic police. METHODS: Identification is based on difference-in-differences methodology, with neighbouring countries serving as a control group. RESULTS: There was a sharp, 33.3%, decrease in accident-related fatalities during the first three post-reform months. This translates into 127 saved lives (95% confidence interval: 51, 204). The decline was, however, temporary; the estimates of the effects going beyond the first year are around zero. Unique data on traffic police activity reveal that police resources devoted to traffic law enforcement gradually declined. CONCLUSIONS: Tougher penalties have significant, but often short-lived effects. Weaker enforcement in the aftermath of such reforms may explain the absence of long-run effects. Language: en

The European commission

Abstract: 2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

Abstract: We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

Climate Change Policy: What Do the Models Tell Us?

Abstract: †Very little. A plethora of integrated assessment models (IAMs) have been constructed and used to estimate the social cost of carbon (SCC) and evaluate alternative abatement policies. These models have crucial flaws that make them close to useless as tools for policy analysis: certain inputs (e.g., the discount rate) are arbitrary, but have huge effects on the SCC estimates the models produce; the models’ descriptions of the impact of climate change are completely ad hoc, with no theoretical or empirical foundation; and the models can tell us nothing about the most important driver of the SCC, the possibility of a catastrophic climate outcome. IAM-based analyses of climate policy create a perception of knowledge and precision, but that perception is illusory and misleading. ( JEL C51, Q54, Q58)

Estimates of the Social Cost of Carbon: Concepts and Results from the DICE-2013R Model and Alternative Approaches

Abstract: The social cost of carbon (SCC) is an important concept for understanding and implementing climate change policies. This term represents the economic cost caused by an additional ton of carbon dioxide emissions (or more succinctly carbon) or its equivalent. The present study describes the development of the concept, provides examples of its use in current US regulator policies, examines its analytical background, and estimates the SCC using an updated integrated assessment model, the DICE-2013R model. The study estimates that the SCC is $18.6 per ton of CO2 in 2005 US dollars and international prices for the current period (2015). For the central case, the real SCC grows at 3% per year over the period to 2050. The major open issues concerning the SCC continue to be the appropriate discount rate, the potential for catastrophic damages, the impact of incomplete harmonization of abatement policies, and the effects of distortionary taxes.