Application of logistic regression models to assess household financial decisions regarding debt

Strzelecka, Agnieszka; Kurdyś-Kujawska, Agnieszka; Zawadzka, Danuta

doi:10.1016/j.procs.2020.09.055

Cited by 21 publications

(15 citation statements)

References 19 publications

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“…. ,x k (which can be both qualitative and quantitative) on the dependent variable Y, which is dichotomous (zero-one variable) [75,76]. In this study it was assumed that the dependent variable Y is the use of external capital to finance agricultural activity.…”

Section: Methodsmentioning

confidence: 99%

Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach

2021

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The aim of this study was to identify and assess the factors influencing the increase in the financial energy of a farm through the use of external capital, taking into account the farmer’s and farm characteristics. For its implementation, a logistic regression model and a classification-regression tree analysis (CRT) were used. The study was conducted on a group of farms in Central Pomerania (Poland) participating in the system of collecting and using data from farms (Farm Accountancy Data Network—FADN). Data on 348 farms were used for the analyses, obtained through a survey conducted in 2020 with the use of a questionnaire. Based on the analysis of the research results presented in the literature to date, it was established that the use of external capital in a farm as a factor increasing financial energy is determined, on the one hand, by the socio-demographic characteristics of the farmer and the characteristics of the farm, and on the other hand, by the availability of external financing sources. Factors relating to the first of these aspects were taken into account in the study. Using the logistic regression model, it was established that the propensity to indebtedness of farms is promoted by the following factors: gender of the head of the household (male, GEND), younger age of the head of the household (AGE), having a successor who will take over the farm in the future (SUC), higher value of generated production (PROD_VALUE), larger farm area (AREA) and multi-directional production of the farm (production diversification), as opposed to targeting plant or animal production only (farm specialization—SPEC). The results of the analysis carried out with the use of classification and regression trees (CRT) showed that the key factors influencing the use of outside capital as a source of financial energy in the agricultural production process are, first of all, features relating to an agricultural holding: the value of generated production (PROD_VALUE), agricultural area (AREA) and production direction (SPEC). The age of the farm manager (AGE) turned out to be of key importance among the farmer’s features favoring the tendency to take debt in order to finance agricultural activity.

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Section: Methodsmentioning

confidence: 99%

Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach

2021

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“…The size and composition of a household and its development phase determine the level and structure of its expenditure, and thus, as the research results prove, they are a factor determining household debt (Chien and DeVaney, 2001;Lee, Lown and Sharpe 2007;Costa and Farinha, 2012;Haq, Ismail, and Mohd Satar, 2018;Jestl, 2019;Strzelecka, Kurdyś-Kujawska and Zawadzka 2020a;Hake and Poyntner, 2020;Intarapak and Supapakorn, 2020).…”

Section: Literature Reviewmentioning

confidence: 98%

“…These people understand the mechanisms of the modern economy to a greater extent, including the credit market's role, and they want to use it (Wałęga, 2012). Research results on the relationship between the level of education and household debt mostly confirm the positive relationship between these variables (Chien and DeVaney, 2001;Lee, Lown and Sharpe 2007;Tan, Yen, Loke, 2011;Wałęga, 2012;Haq, Ismail and Satar, 2018;Strzelecka, Kurdyś-Kujawska and Zawadzka 2020a;Hake and Poyntner, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

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Why Households Borrow Money? Socio-Economic Factors Affecting Households Debts: A Model Approach

Strzelecka¹,

Zawadzka²

2020

ERSJ

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Purpose: This research aims to identify and assess the socioeconomic determinants of Central Pomerania household indebtedness (at the household level) using non-parametric statistical tests and multiple correspondence analysis. Design/Methodology/Approach: The source of data was a survey conducted among 1,000 households of Central Pomerania (Poland). First, it was determined whether there exists a statistically significant relationship between having debt and the socioeconomic characteristics of the households analyzed (using the chi-square test or the Fisher test). Next, a multiple correspondence analysis was used to identify and assess relationships between the categories of features that characterize the surveyed households' indebtedness. Findings: Using non-parametric statistical tests, it was established that there is a statistically significant relationship between debt and the following household characteristics: development phase, size and composition of the household, socioeconomic type, location of the household, a form of residential unit ownership, age of the household head, having economic education by the head of the household, and the level of average monthly income per person in the household. The most often indebted households were those whose main source of income was self-employment, with the number of members exceeding 3 persons and households with dependent children. Practical Implications: The results obtained in this research may be sources of information for credit institutions interested in adjusting the product offer to households' needs because these households-as our research results show-differ in several socioeconomic characteristics. Originality/Value: Our study complements the results of previous research on household debt determinants, confirming the important role of socioeconomic factors in the process of making financial decisions regarding debt.

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“…Logistic Regression is one of the most popular Machine Learning algorithms for binary classification, given a set of independent variables, and is used to predict a binary result (1 or 0, Yes or No, True or False) [32]. It has been applied successfully in various areas, such as Medicine [37], Finance [38], and Economics [39]. In this model, the probabilities describing the possible outcomes of a single trial are modeled using a logistic function, namely the logical relationship between a dichotomous response variable and a series of numerical (continuous, discrete) or categorical explanatory variables.…”

Section: Fundamentals Of the "Logistic Regression" Algorithmmentioning

confidence: 99%

An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus

et al. 2021

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Hybrid models to detect dementia based on Machine Learning can provide accurate diagnoses in individuals with neurological disorders and cognitive complications caused by Human Immunodeficiency Virus (HIV) infection. This study proposes a hybrid approach, using Machine Learning algorithms associated with the multicriteria method of Verbal Decision Analysis (VDA). Dementia, which affects many HIV-infected individuals, refers to neurodevelopmental and mental disorders. Some manuals standardize the information used in the correct detection of neurological disorders with cognitive complications. Among the most common manuals used are the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition) of the American Psychiatric Association and the International Classification of Diseases, 10th edition (ICD-10)—both published by World Health Organization (WHO). The model is designed to explore the predictive of specific data. Furthermore, a well-defined database data set improves and optimizes the diagnostic models sought in the research.

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Application of logistic regression models to assess household financial decisions regarding debt

Cited by 21 publications

References 19 publications

Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach

Debt as a Source of Financial Energy of the Farm—What Causes the Use of External Capital in Financing Agricultural Activity? A Model Approach

Why Households Borrow Money? Socio-Economic Factors Affecting Households Debts: A Model Approach

An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus

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