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The American origin of the French Revolution
Ottinger, Sebastian; Rosenberger, L.
2024 - English
We show that the French combatants’ exposure to the United States increased support for the French Revolution a decade later. French regions from which more American combatants originated had more revolts against feudal institutions, revolutionary societies, volunteers for the revolutionary army, and emigrants from the Old Regime’s elite. To establish causality, we exploit two historical coincidences: i) originally, a French army of seven and a half thousand was ready to sail, but one-third did not, ii) among those deployed, only some regiments were stationed in New England. Only combatants exposed to New England affected the French Revolution after their return.
Keywords:
institutional change; French Revolution; American War of Independence
Fulltext is available at external website.
The American origin of the French Revolution
We show that the French combatants’ exposure to the United States increased support for the French Revolution a decade later. French regions from which more American combatants originated had more ...
Survey expectations, adaptive learning and inflation dynamics
Rychalovska, Y.; Slobodyan, Sergey; Wouters, R.
2024 - English
The use of survey information on inflation expectations as an observable in a DSGE model can substantially refine identification of the shocks that drive inflation. Optimal integration of the survey information improves the model forecast for inflation and for other macroeconomic variables. Models with expectations based on an Adaptive Learning setup can exploit survey information more efficiently than their Rational Expectations counterparts. The resulting time-variation in the perceived inflation target, in inflation persistence, and in the sensitivity of inflation to various shocks provide a rich and consistent description of the joint dynamics of realized and expected inflation. Our framework produces a reasonable interpretation of the post-Covid inflation dynamics. Our learning model successfully identifies the more persistent nature of the recent inflation surge.
Keywords:
inflation; expectations; survey data
Fulltext is available at external website.
Survey expectations, adaptive learning and inflation dynamics
The use of survey information on inflation expectations as an observable in a DSGE model can substantially refine identification of the shocks that drive inflation. Optimal integration of the survey ...
Forced migration and crime: evidence from the 2014 immigration wave to Russia
Shcherbov, Arsenii
2024 - English
Recent years have spurred significant migration movements, underscoring the need to understand their impacts. This study explores a widely-debated correlation between crime and migration. Specifically, I investigate the 2014 migration wave, studying the response of Russian crime rates to the influx of immigrants from Ukraine. I approximate local crime rates using court data on sentencing decisions and describe relevant migration flows with internet search activity. The application of the difference-in-differences method reveals positive effects for property crime sentencing and the heterogeneous response of violent crime sentencing. The findings of this study are policy-relevant and could prove beneficial in understanding and mitigating the effects of future migration waves.
Keywords:
crime; migration; Russia
Fulltext is available at external website.
Forced migration and crime: evidence from the 2014 immigration wave to Russia
Recent years have spurred significant migration movements, underscoring the need to understand their impacts. This study explores a widely-debated correlation between crime and migration. ...
COVID-19 and political preferences through stages of the pandemic: the case of the Czech Republic
Bičáková, Alena; Jurajda, Štěpán
2024 - English
We track the effects of the COVID-19 pandemic on political preferences through ‘high’ and ‘low’ phases of the pandemic. We ask about the effects of the health and the economic costs of the pandemic measured at both personal and municipality levels. Consistent with the literature, we estimate effects suggestive of political accountability of leaders during ‘high’ pandemic phases. However, we also find that the pandemic political accountability effects are mostly short-lived, and do not extend to the first post-pandemic elections.
Keywords:
COVID-19; political preferences; election outcomes
Fulltext is available at external website.
COVID-19 and political preferences through stages of the pandemic: the case of the Czech Republic
We track the effects of the COVID-19 pandemic on political preferences through ‘high’ and ‘low’ phases of the pandemic. We ask about the effects of the health and the economic costs of the pandemic ...
The heterogeneous consequences of reduced labor costs on firm productivity
Del Prato, F.; Zacchia, Paolo
2024 - English
We document how a reduction in labor costs led to heterogeneous effects on the total factor productivity (TFP) of manufacturing firms. Leveraging an Italian labor legislation reform and unique institutional features of the local collective bargaining system, we show that such effects vary along the TFP distribution. Relative to the counterfactual, TFP markedly declines on the left tail, which we explain via selection mechanisms, on the right, TFP mildly increases as firms are able to expand and reallocate their workforce. To guide the evaluation of welfare implications, we develop a general equilibrium model featuring firm selection and frictions in input markets.
Keywords:
labor costs; productivity; collective bargaining
Fulltext is available at external website.
The heterogeneous consequences of reduced labor costs on firm productivity
We document how a reduction in labor costs led to heterogeneous effects on the total factor productivity (TFP) of manufacturing firms. Leveraging an Italian labor legislation reform and unique ...
Matching to suppliers in the production network: an empirical framework
Alfaro-Ureña, A.; Zacchia, Paolo
2024 - English
This paper develops a framework for the empirical analysis of the determinants of input supplier choice on the extensive margin using firm-to-firm transaction data. Building on a theoretical model of production network formation, we characterize the assumptions that enable a transformation of the multinomial logit likelihood function from which the seller fixed effects, which encode the seller marginal costs, vanish. This transformation conditions, for each subnetwork restricted to one supplier industry, on the out-degree of sellers (a sufficient statistic for the seller fixed effect) and the in-degree of buyers (which is pinned down by technology and by “make-or-buy” decisions). This approach delivers a consistent estimator for the effect of dyadic explanatory variables, which in our model are interpreted as matching frictions, on the supplier choice probability. The estimator is easy to implement and in Monte Carlo simulations it outperforms alternatives based on group fixed effects. In an empirical application about the effect of a major Costa Rican infrastructural project on firm-to-firm connections, our approach yields estimates typically much smaller in magnitude than those from naive multinomial logit.
Keywords:
production network; supplier choice; conditional logit
Fulltext is available at external website.
Matching to suppliers in the production network: an empirical framework
This paper develops a framework for the empirical analysis of the determinants of input supplier choice on the extensive margin using firm-to-firm transaction data. Building on a theoretical model of ...
Disappearing stepping stones: technological change and career paths
Kashkarov, Daniil; Artemev, V.
2024 - English
Which career paths lead workers towards high-skilled non-routine cognitive occupations? Using PSID data, we show that, for a significant share of workers, a career path towards non-routine cognitive occupations goes through middle-skilled routine occupations, with the majority going through a subset of routine cognitive occupations. We then argue that the decline in employment in routine cognitive occupations due to routine-biased technological change can negatively affect the chances of younger cohorts joining high-skilled occupations. To test this hypothesis, we develop a structural occupational choice model that endogenously generates realistic career paths and estimate it using PSID data and job ad data from three major US outlets covering the period from 1940 to 2000. Our estimations suggest that, on average, 6% of workers ending up in non-routine cognitive occupations use routine cognitive occupations as stepping stones that allow them to maintain and accumulate human capital and experience relevant for later employment in high-skilled occupations. A fall in employment opportunities in routine cognitive occupations over the period of the most intensive routine-biased technological change led to at least 1.37 million lost high-skilled workers who got stuck in less skilled occupations.
Keywords:
routine-biased technological change; occupational choice; human capital
Fulltext is available at external website.
Disappearing stepping stones: technological change and career paths
Which career paths lead workers towards high-skilled non-routine cognitive occupations? Using PSID data, we show that, for a significant share of workers, a career path towards non-routine cognitive ...
Basic characteristics of sulfide catalysts for the direct decomposition of H2S
Bonnet, Florian; Kaluža, Luděk
2024 - English
Sulfide catalysts are crucial in the hydrodesulfurization (HDS) of petroleum fractions, facilitating the hydrogenolysis of carbon-sulfur bonds. This process generates significant volumes of hydrogen sulfide (H2S), which is typically processed in the Claus unit. However, excess H2S can overwhelm the Claus process, creating both operational and environmental challenges. Researchers are now exploring sulfide catalysts for the direct thermo-catalytic decomposition of H2S to address this issue. Supported catalysts, like Mo/Al2O3, and commercial catalysts, considered typical monolayer-type well-dispersed catalysts, show the highest O2 uptake, ranging from 41.29 μmol/g for MoS2/Al2O3 (KLO) to 58.70 μmol/g for the commercial 715. Unsupported multilayer catalysts, such as Ni/MoWS2 (KKP), exhibit lower O2 uptake at 2.54 μmol/g, though it demonstrates high HDS activity with thiophene. Moreover, O2 uptake effectively describes the sintering of the Mo monolayer phase during the thermocatalytic reaction of H2S at 800°C. These O2 uptakes clearly correlate with the XRD patterns, where the MoS2 phase is X-ray amorphous with an O2 uptake of about 19.04 μmol/g, while the MoS2 phase in the spent catalyst shows certain crystallinity exhibiting an average particle size by Scherrer equation of about 6 nm and the O2 uptake of 1.63 μmol/g. O2 chemisorption thus serves as a valuable measure of the dispersion of Mo sulfides. The results obtain with the study of CoMo/Al2O3 (KJJ-family catalysts), highlight the correlation between the increasing amount of adsorbed O2 with the increasing nominal loading of MoO3 and the increasing rate constant of thiophene kTH. This research reveals the potential of these catalysts in hydrocarbon refining. The findings underline the connection between catalytic chemistry, process engineering, and environmental sustainability, with the objective to enhance industrial refining processes.
Keywords:
sulfide catalyst; O2 chemisorption; H2S decomposition
Available at various institutes of the ASCR
Basic characteristics of sulfide catalysts for the direct decomposition of H2S
Sulfide catalysts are crucial in the hydrodesulfurization (HDS) of petroleum fractions, facilitating the hydrogenolysis of carbon-sulfur bonds. This process generates significant volumes of hydrogen ...
Financial skills and search in the mortgage market
Cota, Marta; Šterc, Ante
2024 - English
Are households with low financial skills disadvantaged in the mortgage market? Using stochastic record linking, we construct a unique U.S. dataset encompassing a rich set of mortgage details and borrowers’ characteristics, including their objective financial literacy measure. We find that households with low financial literacy are up to 4% more likely to search less and lock in at 15-20 b.p. higher rates. Upon origination, unskilled borrowers face a 35-45% higher mortgage delinquency and end up with a 30% lower likelihood of refinancing. Overall, for a $100,000 loan, the potential losses from low financial literacy are more than $9,329 over the mortgage duration. To understand how financial education, more accessible mortgages, or mortgage rate changes affect households with low financial literacy, we formulate and calibrate a mortgage search model with heterogeneous search frictions and endogenous financial skills. Our model estimates show that search intensity and financial skill variations contribute to 55% and 10% of mortgage rate variations, respectively. We find that i) more accessible mortgages lead to a higher delinquency risk among low-skilled households, ii) financial education mitigates the adverse effects of increased accessibility, and iii) low mortgage rates favor high-skilled homeowners and, by reinforcing refinancing activity, deepen consumption differences across different financial skill levels.
Keywords:
mortgage refinancing; mortgage search; financial skills
Fulltext is available at external website.
Financial skills and search in the mortgage market
Are households with low financial skills disadvantaged in the mortgage market? Using stochastic record linking, we construct a unique U.S. dataset encompassing a rich set of mortgage details and ...
Some modifications of the limited-memory variable metric optimization methods
Vlček, Jan; Lukšan, Ladislav
2023 - English
Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric rank-one (SR1) update formula is derived in a similar way as for the block BFGS update in Vlˇcek and Lukˇsan (Numerical Algorithms 2019). The block SR1 formula is then modified to obtain an update which can reduce the required number of arithmetic operations per iteration. Since it usually violates the corresponding secant conditions, this update is combined with the shifting investigated in Vlˇcek and Lukˇsan (J. Comput. Appl. Math. 2006). Moreover, a new efficient way how to realize the limited-memory shifted BFGS method is proposed. For a class of methods based on the generalized shifted economy BFGS update, global convergence is established. A numerical comparison with the standard L-BFGS and BNS methods is given.
Keywords:
unconstrained minimization; variable metric methods; limited-memory methods; variationally derived methods; arithmetic operations reduction; global convergence
Available in a digital repository NRGL
Some modifications of the limited-memory variable metric optimization methods
Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric ...
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