Why do households participate in the loan moratorium in Hungary? Theoretical and empirical considerations

In order to mitigate the economic effects from the COVID-19 epidemic, a moratorium on loan repayments was introduced in several countries, including Hungary. Essentially, a loan moratorium provides additional finance for participants, allowing theories of both credit demand and consumption to be tested on debtors’ decisions as to whether or not they participate in the programme. In this paper, we use a linear probability model on the Hungarian survey data to examine the driving factors behind the households’ decision to participate in the scheme. Our results show that the younger debtors and those with more children are more likely to utilise the programme. Stretched financial situations, i.e., lower incomes, lower savings and higher payment-to-income ratios, increase the probability of continued participation as well. The chance of participating in the scheme also increases significantly when a household has faced borrowing constraints over the past two years, i.e., it has not been or only partially been able to satisfy its credit demand.

Sibling Models, Categorical Outcomes, and the Intra-Class Correlation

In sibling models with categorical outcomes the question arises of how best to calculate the intraclass correlation, ICC. We show that, for this purpose, the random effects linear probability model is preferable to a random effects non-linear probability model, such as a logit or probit. This is because, for a binary outcome, the ICC derived from a random effects linear probability model is a non-parametric estimate of the ICC, equivalent to a statistic called Cohen’s κ. Furthermore, because κ can be calculated when the outcome has more than two categories, we can use the random effects linear probability model to compute a single ICC in cases with more than two outcome categories. Lastly, ICCs are often compared between groups to show the degree to which sibling differences vary between groups: we show that when the outcome is categorical these comparisons are invalid. We suggest alternative measures for this purpose.

The Soviet Informal Economy as a Factor of Post-Soviet Development

The article analyzes the quantitative relationship between the informal economy in the Soviet republics of the 1980s and the characteristics of the market economy in these republics after the collapse of the Soviet Union. Methodologically, the study relies on the logit, linear probability model and least-squares method. The logit and linear probability model are used to quantify the fixed effects affecting the attitudes of households in different countries in the 2000s to the market economy in comparison with the planned economy. The authors compare the obtained fixed effects with the size of the informal economy in Soviet republics of the 1980s using the least-squares method. The study shows a direct relationship between people’s involvement in the Soviet informal sector and their subsequent adaptability to the new conditions of the market economy after the collapse of the Soviet Union. Thus, the possible positive impact of the informal economy on the adaptation of the population to the market economy is empirically proved. The authors conclude that the Soviet informal economy helped facilitate households’ transition to the market economy and in the medium term had a positive impact on post-Soviet economic development.

Charged with Instability: Are Paternal Arrests and Criminal Charges Enough to Shake the Marital Stability of American Couples?

With the growing rate of divorce, increasing efforts are being made to identify the factors that contribute to relationship dissolution for many American couples. One commonly noted, and particularly concerning, factor toward relationship instability is the incarceration of husbands and fathers. Although paternal incarceration and familial stability have been studied, little is known about the relationship between criminal charges and divorce. The current study utilized data from the Fragile Families and Child Wellbeing Study to understand the effect of paternal criminal charges on divorce for 725 families. Utilizing a logistic regression and two-stage least squares linear probability model, results show that, even without incarceration, being charged with a crime as a husband significantly increases the likelihood that a couple will get divorced. These findings have significant implications for understanding how encounters with the criminal justice system affect familial well-being and stability.

Analisis Prediksi Kemungkinan Pergantian Auditor Pada Perusahaan Properti Dengan Menggunakan Linear Probability Model

This study aims to analyze the prediction of the possibility of an auditor switching in property companies listed on the Indonesia Stock Exchange in 2017 based on the Public Accountant Firm’s size and management switching using a linear probability model. The data used are secondary data obtained from the financial statements of property companies. Property companies that meet the requirements in the study as a sample of 33 companies. To estimate the linear probability model using the ordinary least square method. The model that has been obtained was tested by t-test and F test. The results of the data analysis can be concluded that the model obtained can be used to predict the possibility of a property company auditor switching based on the predictor variable of Public Accountant Firm’s size and management switching with a predictive reliability level of 84.84%. Keywords: linear probability model, auditor switching, Public Accountant Firm’s size, management switching, ordinary least square method.

The First Systematic Survey of Restaurant Hygiene in Paris, 1908

In 1908, an unpublished investigation by the French government discovered a number of commercial kitchens that violated the 1903 law regarding hygiene and security in the workplace. A linear-probability model shows that restaurants in tourist neighborhoods were 12 percentage points more likely to transgress sanitary regulations than those in non-tourist areas. Many of the kitchens in the expensive restaurants of central Paris were in basements where they lacked fresh air, sunlight, and efficient waste evacuation. Clientele also mattered as a determinant of insalubrity. Local repeat customers whose loyalty depended on constant restaurant standards tended to exert more pressure on sanitation than did tourists who based their choices on culinary reputation, such as recommendations in Baedeker’s travel guide.

Pengaruh Faktor Sosial Ekonomi terhadap Perkawinan Muslim di Indonesia

This study aims to find out what factors that affect a Muslim's decision to get married. This study uses the data from the Indonesian Family Life Survey (IFLS) with a quantitative approach using 83% of the sample population in Indonesia covering approximately 30,000 people taken in 13 of the 27 provinces in Indonesia. This study was analyzed using Linear Probability Model (LPM) regression, Logit regression and Probit regression. The data in this study were processed using STATA MP software. According to the results of data using three regression models, the factors that affect the decision of each individual in Indonesia in general to marry are gender, religion, age, education and occupation. The factors that affect each individual Muslim in Indonesia to make a decision to marry are gender, age, education and occupation. Then, for women in Indonesia in general, the factors that affect the decision to get married are religion, age, and occupation. Last but not least, for Muslim women, the factors that affect the decision to marry is age and occupation.Keywords: Socio-Economy, Muslim Marriage, Marital Decision