This study delves into the intricate relationship between corporate innovation and public support, underscoring innovation's vital role in driving economic growth and competitiveness. Recognizing the multifaceted nature of innovation, from product and process improvements to organizational and...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

In the literature on Philippine public procurement, knowledge gaps exist in terms of coverage of period of reform implementation and scope of reform application. This study helps close these gaps by analyzing Philippine public procurement history up to the years of application of the 2016...

We examined the relationships between the compositional changes in demographic and socioeconomic factors and the changes in the prevalence of material deprivation in rural and urban areas in Poland. Using the European Union Statistics on Income and Living Conditions (EU-SILC) data for 2019-2020,...

This paper aims to understand the health effects of energy poverty in Germany using SOEP panel data from 2010 to 2020. Linear probability models and fixed effects ordered logit models reveal a consistently negative relationship of three expendituresbased energy poverty indicators with general...

This paper aims to understand the health effects of energy poverty in Germany using SOEP panel data from 2010 to 2020. Linear probability models and fixed effects ordered logit models reveal a consistently negative relationship of three expenditures based energy poverty indicators with general...

Using a discrete choice experiment (DCE), we analyze how social comparisons and financial information influence households' preferences and trade-offs among three sustainable electricity demand behaviors: conservation actions, efficiency investments, and purchasing a green power mix. Our results...

The spatial distribution of future renewable capacities is a key determinant for developing appropriate grid expansion plans. This is particularly relevant for onshore wind energy. Existing studies mostly extrapolate future installations based on existing capacities and available sites. As wind...

According to the Federal Reserve of the United States, in the second quarter of 2024, American credit card debt reached USD 1.14 trillion, the highest balance ever recorded. In an age of high-interest, complex credit cards, how does financial literacy affect credit card debt repayment? Also, how...

In this paper we provide an empirical analysis of German casino locations. Due to the "mercantilistic background" of casinos, we assume that casinos are more likely to be found at borders and tourist areas. Although the location decision has been made in the past, we use cross-sectional data at...

This paper studies for the first time the links between interbank liability and equity markets (financial exposure), and mergers and acquisitions (M&As) in the European banking sector, both at the micro and macro level. Using a binary logit model, the paper first examines - at the micro level -...

Saving is an important factor in households' welfare in developing countries. However, most studies have focused on urban areas and at the macroeconomic level. Consequently, such studies mask the reality of rural households, which constitute a large proportion in Ethiopia. Hence, this study aims...

Nowadays, poverty is one of the most important issues that needs due attention in many developing countries like Ethiopia. Nonetheless, poverty in Ethiopia remains widespread in both rural and urban areas. Therefore, this study aimed to examine the determinants and status of poverty in Berehet...

In this study we develop an early warning system (EWS) to forecast currency crises in emerging countries in Asia and Latin America, using logit regression on monthly data from 1992 to 2011. We found that macroeconomic and institutional variables are valuable indicators for forecasting crises....

Urban areas confront a chronic shortage of housing, especially in the low-rent segment. This precarious situation is further exacerbated by major challenges, like the destruction of housing by wars and natural catastrophes, rapid increase of demand, or pandemics cutting incomes. In response, the...

We study cluster-robust inference for binary response models. Inference based on the most commonly-used cluster-robust variance matrix estimator (CRVE) can be very unreliable. We study several alternatives. Conceptually the simplest of these, but also the most computationally demanding, involves...

Regression discontinuity is a popular tool for analyzing economic policies or treatment interventions. This research extends the classic static RD model to a dynamic framework, where observations are eligible for repeated RD events and, therefore, treatments. Such dynamics often complicate the...

Predicting freeway traffic states is, so far, based on predicting speeds or traffic volumes with various methodological approaches ranging from statistical modeling to deep learning. Traffic on freeways, however, follows specific patterns in space-time, such as stop-and-go waves or mega jams....

Discrete choice experiments (DCEs) often present concise choice scenarios that may appear incomplete to respondents. To allow respondents to express uncertainty arising from this incompleteness, DCEs may ask them to state probabilities with which they expect to make specific choices. The...

We estimate the labor market power of over 13,000 manufacturing establishments across 82 low and middle-income countries around the world. Within local labor markets, larger and more productive firms have higher wage markdowns and pay lower wages. Labor market power across countries exhibits a...

This paper proposes a new approach to identification of the semiparametric multinomial choice model with fixed effects. The framework employed is the semiparametric version of the traditional multinomial logit with the fixed-effects model (Chamberlain (1980)). This semiparametric multinomial...

This study employs six Machine Learning methods - Logit, Lasso-Logit, Ridge-Logit, Random Forest, Extreme Gradient Boosting, and an Ensemble - alongside registry data on abortions in Spain from 2011-2019 to predict multiple abortions and assess monetary savings through targeted interventions. We...

We analyse how reversals of several types of capital flows impact currency crises in emerging market and developing economies. Estimates of logit models show that reversals of (equity and debt) portfolio flows significantly increase the likelihood of currency crises in emerging market economies....

In this paper, we use novel firm-level microdata for Ireland to explore the factors that determine the investment in digitalisation for micro, small and medium-sized enterprises (SMEs). More specifically, we use cross-sectional survey data to explore whether firm fundamentals or constraints act...