Modeling debt choice in agriculture: the effect of endogenous asset values

2017 ◽  
Vol 77 (1) ◽  
pp. 95-110 ◽  
Author(s):  
Maria Bampasidou ◽  
Ashok K. Mishra ◽  
Charles B. Moss
Keyword(s):  
Panel Data ◽  
Interest Rate ◽  
Agricultural Sector ◽  
Macroeconomic Policy ◽  
Rate Of Return ◽  
Data Set ◽  
Content Type ◽  
Asset Values ◽  
The Usa ◽  
Non Parametric

Purpose The purpose of this paper is to investigate the endogeneity of asset values and how it relates to farm financial stress in US agriculture. The authors conceptualize an implied measure of farm financial stress as a function of debt position. The authors posit that there are variations in the asset values that are beyond the farmer’s control and therefore have implications on farm debt. Design/methodology/approach The framework recognizes the endogeneity of return on assets (ROA). It uses a non-parametric technique to approximate the variance of expected ROA (VEROA). The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Further, the authors use a dynamic balanced panel data set from 1960 to 2011 for 15 US agricultural states from the Agricultural Resource Management Survey, and information from traditional state-level financial statements. Findings Estimation of linear dynamic debt panel data models accounting for the endogeneity of ROA and VEROA is a challenging task. Estimated variances are unstable. Hence, the authors focus on variance specification that uses the residuals squared from the ARIMA specification and non-parametric estimators. Arellano-Bover/Blundell-Bond generalized method of moments estimation procedures, although may be biased, show that VEROA has a negative and significant effect on the total amount of debt in the agricultural sector. Research limitations/implications The instruments used in this analysis are lagged regressors which may be weakly correlated with the relevant first-order condition, hence not properly identifying the parameters of interest. Future research could include the identification of better instruments, potentially use of sequential moment conditions. Originality/value Unlike previous study, the authors use non-parametric approximation of VEROA. The authors model the rate of return on agricultural assets and interest rate with a formulation that focuses on macroeconomic policy. Second, the authors make use of a large dynamic balanced panel data set from 1960 to 2011 for 15 agricultural states in the USA. To the best of the authors’ knowledge, this study is one of the few that provides evidence on risk-balancing behavior at the agricultural sector level, of the USA.

scholarly journals Sector size, technical change and stability in the USA (1957-2006): a Schumpeterian approach

2014 ◽  
Vol 41 (10) ◽  
pp. 956-974 ◽  
Author(s):  
Konstantinos Konstantakis ◽  
Panayotis G. Michaelides ◽  
Theofanis Papageorgiou
Keyword(s):  
Panel Data ◽  
Technological Change ◽  
Economic Activity ◽  
Economic Recession ◽  
Data Set ◽  
Content Type ◽  
Us Economy ◽  
Data Framework ◽  
The Us ◽  
The Usa

Purpose – The purpose of this paper is to investigate two famous postulates of the Schumpeterian doctrine and its implications for the US economy. Design/methodology/approach – Analytically, the authors investigate whether sector size matters for sectoral: technological change and stability, as expressed through the relevant quantitative measures and variables. To this end, the authors test a number of relevant models that express the various forms of this relationship. More precisely, the authors use panel data for the 14 main sectors of economic activity in the USA over the period 1957-2006, just before the first signs of the US and global recession made their appearance. Findings – The results seem to be in line with the Schumpeterian postulate that market size matters for technological change and economic stability, for the US economy (1957-2006). Clearly, further research would be of great interest. Originality/value – This work contributes to the literature in the following ways: first, it provides an extensive review of the literature on the subject and adopts two relevant methodological approaches. Second, based on these quantitative approaches, the paper offers a complete investigation of two famous postulates of the Schumpeterian theory for the US economy, and it is the first, to the best of the authors’ knowledge, to do so by sector of economic activity, in a panel data framework. Third, the paper uses a wide data set (1957-2006) to examine the US economy up until the first signs of the US and global economic recession made their appearance.

Financial and other frauds in the United States: a panel analysis approach

2017 ◽  
Vol 25 (4) ◽  
pp. 413-433 ◽  
Author(s):  
Shuming Bai ◽  
Kai S. Koong
Keyword(s):  
Panel Data ◽  
Panel Data Analysis ◽  
The United States ◽  
Three Dimensions ◽  
Panel Analysis ◽  
Cross Sectional ◽  
Data Set ◽  
Sentinel Network ◽  
Content Type ◽  
The Usa

Purpose The purpose of this paper is to report on the findings and implications associated with the millions of financial and other fraud complaints that are reported to the Federal Trade Commission and published in the Consumer Sentinel Network Data Book each year since 2002. Based on the three dimensions, namely, the number of complaints, growth rates and geographic locations of those crimes, this study found similar as well as unique trends that are new and are critical for addressing the rise of cybercrimes in the USA. The trends and patterns identified may also have implications for addressing cybercrimes in other parts of the world. Design/methodology/approach This research is a cross-sectional time-series study that covers frauds and cybercrimes in the USA from 2002 to 2015. The observed cases included the number of total complaints, complaints categories and payment amount or loss incurred both at the national and state levels. First, aggregate fraud totals, categories, payments and payment methods were analyzed and ranked. Second, state data for fraud categories, payments and filing rate per capita were organized into panel data for analysis, comparison and ranking. This cross-sectional and longitudinal approach of the different dimensions of financial and other frauds generate new rankings and more robust results. Findings The key findings are related to the long-term occurrences and trends of financial and online frauds in the USA. While some general trends are consistent with prior studies, the cross-sectional and longitudinal panel analysis produced some unique results. States that reported the most complaints do not necessarily rank high when examined with their growth per capital or their rates of growth. Their rankings could change dramatically due to other factors. In addition, eight of the top ten crime categories are the same both at the national and state levels, indicating that law enforcement could target the same crime categories. Originality/value The panel data analysis is new (first attempt at using this technique on the data set) and robust because it allows cross-sectional and longitudinally analysis of the various financial and online fraud crimes, in aggregate and by state, for a more comprehensive and comparative examination of the fraud behavioral trends. This research can be viewed as an improvement over earlier studies because the panel analysis identifies what fraud trends, scam types and payment amount exist on the national and state levels. The rate of fraud growth in the respective states provides a better understanding about future development of this problem.

Central bank transparency, inflation targeting and monetary policy: a panel data approach

2018 ◽  
Vol 45 (6) ◽  
pp. 1159-1174 ◽  
Author(s):  
Gabriel Caldas Montes ◽  
Cristiane Gea
Keyword(s):  
Developing Countries ◽  
Monetary Policy ◽  
Panel Data ◽  
Interest Rate ◽  
Central Bank ◽  
Interest Rates ◽  
Inflation Targeting ◽  
Content Type ◽  
Central Bank Transparency ◽  
Policy Interest

Purpose The evidence concerning the effects of the inflation targeting (IT) regime as well as greater central bank transparency on monetary policy interest rates is not conclusive, and the following questions remain open. What is the effect of adopting IT on both the level and volatility of monetary policy interest rate? Does central bank transparency affect the level of the monetary policy interest rate and its volatility? Are these effects greater in developing countries? The purpose of this paper is to contribute to the literature by answering these questions. Hence, the paper analyzes the effects of IT and central bank transparency on monetary policy. Design/methodology/approach The analysis uses a sample of 48 countries (31 developing) comprising the period between 1998 and 2014. Based on panel data methodology, estimates are made for the full sample, and then for the sample of developing countries. Findings Countries that adopt the IT regime tend to have lower levels of monetary policy interest rates, as well as lower interest rate volatility. The effect of adopting IT on both the level and volatility of the basic interest rate is smaller in developing countries. Besides, countries with more transparent central banks have lower levels of monetary policy interest rates, as well as lower interest rate volatility. In turn, the effect of central bank transparency on both the level and volatility of the basic interest rate is greater in developing countries. Practical implications The study brings important practical implications regarding the influence of both the IT regime and central bank transparency on monetary policy. Originality/value Studies have sought to analyze whether IT and central bank transparency are effective to control inflation. However, few studies analyze the influence of IT and central bank transparency on interest rates. This study differs from the few existing studies since: the analysis is done not only for the effect of transparency on the level of the monetary policy interest rate, but also on its volatility; the central bank transparency index that is used has never been utilized in this sort of analysis; and the study uses panel data methodology, and compares the results between different samples.

Knowledge management and social entrepreneurship education: lessons learned from an exploratory two-country study

2019 ◽  
Vol 23 (10) ◽  
pp. 1984-2006 ◽  
Author(s):  
George Thomas Solomon ◽  
Nawaf Alabduljader ◽  
Ravi S. Ramani
Keyword(s):  
Knowledge Management ◽  
Social Entrepreneurship ◽  
Social Issues ◽  
Entrepreneurship Education ◽  
Growth Potential ◽  
Data Set ◽  
Content Type ◽  
Course Offerings ◽  
The Future ◽  
The Usa

Purpose Social entrepreneurship courses are among the fastest growing category of course offerings to entrepreneurship students (Brock and Kim, 2011) because both high growth potential- and steady growth-social ventures can create value and help solve social issues effectively and efficiently. As knowledge disseminators, entrepreneurship educators are in prime position to develop the knowledge, skills and abilities of students, which, in turn, increases their intentions to start a social venture and their ability to manage and grow their venture. Students gain an understanding about the role of entrepreneurship in addressing social opportunities, as well as knowledge related to starting, managing and growing social entrepreneurship ventures. This paper is divided into three parts. First, the authors broadly discuss the concept of social entrepreneurship. Second, the authors present an overview of the field of social entrepreneurship education (SEE) and its evolution. Finally, the authors supplement this review with an analytical examination of SEE, in which the authors present results of a cross-country analysis survey of over 200 entrepreneurship education programs in the USA and Canada. This paper aims to present information about: student enrollment in social entrepreneurship courses in comparison to other entrepreneurship courses; the frequency of offering social entrepreneurship courses and programs compared to other entrepreneurship courses and programs; and future trends in SEE. The results revealed a strong demand for social entrepreneurship from students, room for improvement in terms of the supply of course offerings, and a strong belief in the continued growth of social entrepreneurship. The authors conclude with suggestions about the future of SEE. Design/methodology/approach Analysis of secondary data derived from the oldest and most-frequently cited sources regarding entrepreneurship education in the USA and a novel data set examining entrepreneurship education in Canada. Both data sets were collected using an online self-report survey. Findings Demand for SEE continues to rise in both the USA and Canada. However, course and program offerings have not kept pace. Prominent trends in social entrepreneurship such as cross-campus programs and addressing the evolving demographics of students in higher education institutions need more attention. Originality/value A cross-cultural study of SEE that provides a high-level view of the state of the field today. In addition, the paper outlines the potential of the field of knowledge management for the future of SEE.

scholarly journals Translating emotional insights from hospitality employees’ comments

2018 ◽  
Vol 32 (1) ◽  
pp. 75-92 ◽  
Author(s):  
Lisa M. Young ◽  
Swapnil Rajendra Gavade
Keyword(s):  
Job Satisfaction ◽  
Sentiment Analysis ◽  
Big Data Analytics ◽  
Large Data ◽  
Hospitality Management ◽  
Data Set ◽  
Employee Survey ◽  
Content Type ◽  
Employee Job Satisfaction ◽  
The Usa

PurposeThe purpose of this paper is to use the data analysis method of sentiment analysis to improve the understanding of a large data set of employee comments from an annual employee job satisfaction survey of a US hospitality organization.Design/methodology/approachSentiment analysis is used to examine the employee comments by identifying meaningful patterns, frequently used words and emotions. The statistical computing language, R, uses the sentiment analysis process to scan each employee survey comment, compare the words with the predefined word dictionary and classify the employee comments into the appropriate emotion category.FindingsEmployee responses written in English and in Spanish are compared with significant differences identified between the two groups, triggering further investigation of the Spanish comments. Sentiment analysis was then conducted on the Spanish comments comparing two groups, front-of-house vs back-of-house employees and employees with male supervisors vs female supervisors. Results from the analysis of employee comments written in Spanish point to higher scores for job sadness and anger. The negative comments referred to desires for improved healthcare, requests for increased wages and frustration with difficult supervisor relationships. The findings from this study add to the growing body of literature that has begun to focus on the unique work experiences of Latino employees in the USA.Originality/valueThis is the first study to examine a large unstructured English and Spanish text database from a hospitality organization’s employee job satisfaction surveys using sentiment analysis. Applying this big data analytics process to advance new insights into the human capital aspects of hospitality management is intriguing to many researchers. The results of this study demonstrate an issue that needs to be further investigated particularly considering the hospitality industry’s employee demographics.

Exchange rate effects on agricultural exports

2019 ◽  
Vol 11 (4) ◽  
pp. 600-621
Author(s):  
Rui Mao
Keyword(s):  
Exchange Rate ◽  
Panel Data ◽  
Exchange Rates ◽  
Food Industry ◽  
Real Exchange Rates ◽  
Data Set ◽  
Content Type ◽  
Agricultural Exports ◽  
Country Level ◽  
Rate Effects

Purpose The purpose of this paper is to extend empirical investigations of the relationship between real exchange rates and agricultural exports to the firm-product-country level with the use of disaggregated panel data of China’s food industry. In particular, the study aims to explore heterogeneities in the export response to real exchange rates across firms, destinations and products, as well as to differentiate responses on the intensive and extensive margins. Design/methodology/approach This paper utilizes a merged panel data set of firm-product-country level transaction records of China’s agricultural exports with firm-level survey data of the food industry. Panel regression models are constructed to identify empirical relationships. Findings Real appreciations are found to reduce export quantities and the probability to enter destination markets. These impacts are enhanced in 2005 when China unexpectedly depegged yuan from the USD. In addition, real appreciations in 2005 also reduced the yuan-denominated export price and increased firms’ probability to exit destination markets. Taking the exchange rate reform as a natural experiment, evidence suggests that the negative exchange rate effects on exports are robust to the endogeneity issue. Finally, heterogeneous export responses are identified with respect to firm productivities and ownerships, income levels and locations of destination markets, as well as product groups. Originality/value This paper provides first-hand evidence on how real exchange rates influence agricultural exports at the firm-product-country level. A featured contribution is that China’s exchange rate reform in 2005 is utilized to alleviate the typical concern of endogeneity. Findings may benefit policy makers, for example, by identifying firms most vulnerable to real appreciations.

Board gender diversity and US corporate bonds

2019 ◽  
Vol 15 (5) ◽  
pp. 771-791 ◽  
Author(s):  
Renee M. Oyotode-Adebile ◽  
Zubair Ali Raja
Keyword(s):  
Panel Data ◽  
Propensity Score ◽  
Design Methodology ◽  
Gender Diversity ◽  
Data Set ◽  
Content Type ◽  
Gender Diverse ◽  
Board Gender Diversity ◽  
The Impact ◽  
Women Participation

Purpose The purpose of this paper is to examine the impact of board gender diversity on bond terms and bondholders’ returns. Design/methodology/approach The authors perform pooled OLS regression, simultaneous regressions and propensity score matching to a panel data set of bond data for 319 US firms from 2007 to 2014. Findings The authors find that firms with gender-diverse boards have lower yields, higher ratings, larger issue size and shorter maturity. They also find that bondholders require fewer returns from firms with gender-diverse boards. However, the effect is more pronounced when women, constitutes at least 29.67 percent of the board. Originality/value This analysis supplements the findings that board gender diversity is essential for bondholders. It shows that bondholders should look at board gender diversity as a criterion to invest because bonds issued by firms with gender-diverse board have less risk. For practitioners, this study shows that more women participation on boards leads to a reduction in borrowing costs.

An analysis of operating expense control within US multifamily properties

2017 ◽  
Vol 35 (1) ◽  
pp. 48-66 ◽  
Author(s):  
Andrew Carswell
Keyword(s):  
Explanatory Variable ◽  
Rental Housing ◽  
Positive Association ◽  
Individual Investors ◽  
Property Management ◽  
Property Market ◽  
Data Set ◽  
Content Type ◽  
Operating Income ◽  
The Usa

Purpose The purpose of this paper is to determine the effect that ownership and management structures have on ability to control operating expenses. For individual investors, intensity of management experience is also explored as a possible explanatory variable for operating expenses. For property management services that are contracted out, the level of the fee is investigated as a possible cause for movements in operating expenses as well. Finally, operating expenses are used as a possible explanatory variable for a property’s lease-up performance during the year. Design/methodology/approach The analysis consists of a series of regression models performed on data provided by the 2012 Rental Housing Finance Survey (RHFS) in the USA. The RHFS is a unique data set that covers a wide degree of information on multifamily properties. The RHFS represents 2,260 properties in total, and covers various aspects of the apartment industry, including financing and operational cost measures. Control variables used as independent variables include number of units, year of property acquisition, and age of building. Findings Individual ownership and self-management proved to be statistically significant drivers in driving down log operating expenses. Hours spent by individuals performing property management roles on their own properties had a slightly positive association with operating expenses. For professional managers, the fees devoted solely to the manager or management company had a highly significant and positive effect on other operating costs. Finally, when separating out the individual components of operating expenses, only two variables had significant effects on tenant lease-ups: management expenses (positive) and security expenses (negative). Research limitations/implications The data set is potentially biased toward those properties with less than 100 units, and thus it would be problematic to assume that these findings are generalizable to the population at large. There are also no geographic coding indicators within the RHFS data set, which eliminates the potential to control for various market factors and rural/urban differences. Practical implications The research provides an understanding of some of the basic factors behind increases in operating expenses, which ultimately has implications for performance benchmarks such as net operating income and property market value. Social implications The reasonable controlling of operating expenses ultimately has potentially positive implications for low- to moderate-income populations, who would ultimately experience lower rents as a result. Originality/value This research represents one of the first known uses of the RHFS database.

How loan interest rate liberalization affects firms’ loan maturity structure

2014 ◽  
Vol 4 (2) ◽  
pp. 153-167 ◽  
Author(s):  
Jianfang Zhou ◽  
Jingjing Wang ◽  
Jianping Ding
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Manufacturing Companies ◽  
Short Term ◽  
Data Set ◽  
Content Type ◽  
Interest Rate Liberalization ◽  
Upper Limit ◽  
Maturity Structure

Purpose – After loan interest rate upper limit deregulation in October 2004, the financing environment in China changed dramatically, and the banks were eligible for risk compensation. The purpose of this paper is to focus on the influence of the loan interest rate liberalization on firms’ loan maturity structure. Design/methodology/approach – Based on Rajan's (1992) model, the authors constructed a trade-off model of how the banks choose long-term and short-term loans scales, and further analyzed banks’ loan term decisions under the loan interest rate upper limit deregulation or collateral cases. Then the authors used an unbalanced panel data set of 586 Chinese listed manufacturing companies and 9,376 observations during the period 1996-2011 to testify the theoretical conclusion. Furthermore, the authors studied the effect on firms with different characteristics of ownership or scale. Findings – The results show that the loan interest rate liberalization significantly decreases the private companies’ reliance on short-term loans and increases sensitivity to interest rates of state-owned companies’ long-term loans. But the results also show that the companies’ ownership still plays a key role on the long-term loans availability. When monetary policy tightened, small companies still have to borrow short-term loans for long-term purposes. As the bank industry is still dominated by state-owned banks and the deposit interest rate has upper limits, the effect of the loan interest rate liberalization on easing long-term credit constraints is limited. Originality/value – From a new perspective, the content and findings of this paper contribute to the study of the effect of the interest rate liberalization on China economy.

scholarly journals Impact of the Basel III bank regulation on US agricultural lending

2020 ◽  
Vol 80 (3) ◽  
pp. 321-337 ◽  
Author(s):  
Kevin Nooree Kim ◽  
Ani L. Katchova
Keyword(s):  
Growth Rates ◽  
Banking Sector ◽  
Agricultural Sector ◽  
Global Financial Crisis ◽  
Detailed Examination ◽  
Capital Requirements ◽  
Basel Iii ◽  
Content Type ◽  
The Usa ◽  
The Impact

Purpose Following the recent global financial crisis, US regulatory agencies issued laws to implement the Basel III accords to ensure the resiliency of the US banking sector. Theories predict that enhanced regulations may alter credit issuance of the regulated banks due to increased capital requirements, but the direction of changes might not be straightforward especially with respect to the agricultural loans. A decrease in credit availability from banks might pose a serious problem for farmers who rely on bank credit especially during economic recessions. The paper aims to discuss these issues. Design/methodology/approach In this study, the impact of Basel III regulatory framework implementation on agricultural lending in the USA is examined. Using panel data of FDIC-insured banks from 2008 to 2017, the agricultural loan volume and growth rates are examined for agricultural banks and all US banks. Findings The results show that agricultural loan growth rates have slowed down, but the amount of agricultural loan volume issuance still remained positive. More detailed examination finds that regulated agricultural banks have decreased both the agricultural loan volume and their loan exposure to the agricultural sector, showing a possible sign of credit crunch. Originality/value This study examines whether the implementation of the Basel III regulation has resulted in changes in agricultural loan issuance by US banks as predicted by the lending channel theory.

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