Monetary policy and food price inflation: A wavelet-based quantile regression analysis

PurposeThe management of liquidity has always been seen as a critical but often ignored issue in finance. Despite the abundance of studies on liquidity management, these studies mainly focus on developed countries and on large firms. Liquidity is critical for the small firm but studies on liquidity management in small and medium enterprises (SMEs) are lacking. The purpose of this paper is to examine the firm-level determinants of liquidity of SMEs in Malaysia.Design/methodology/approachData are collected for a total of 986 small firms in Malaysia from 2011 to 2014, resulting in a total of 2,683 observations. Firm-specific variables and the effect of the economy are considered as the possible determinants of liquidity. Ordinary least squares (OLS) regression analysis with standard errors adjusted for firm-level clustering and quantile regression analysis are used for this purpose.FindingsAnalysis using OLS regression technique indicates that a firm’s profitability, its growth, asset tangibility, size, age and firm status are significant factors in influencing its liquidity decision. Leverage and economic condition are not found to have any significant influence on liquidity. However, quantile regression analysis provides a different picture especially for SMEs with liquidity at the quantile levels ofθ=0.10 and 0.90. Atθ=0.10, only profitability, tangibility and firm status are significant, while atθ=0.90, tangibility, size, firm status and, to some extent, age are significant in influencing liquidity levels.Originality/valueTo the author’s knowledge, this is the first study analyzing the liquidity decision of SMEs in an emerging market such as Malaysia. Most studies on liquidity management of SMEs are focused on developed countries due to data availability but these studies are also only a handful. Additionally, this study uses quantile regression analysis which highlights the need to analyze financial decisions at different levels rather than at the aggregate level as done in OLS regression analysis.

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The effects of medical factors on transfer deficits in Public Assistance in Japan: a quantile regression analysis

International Journal of Health Care Finance and Economics ◽

10.1007/s10754-011-9098-2 ◽

2011 ◽

Vol 11 (4) ◽

pp. 287-307 ◽

Cited By ~ 3

Author(s):

Masayoshi Hayashi

Keyword(s):

Regression Analysis ◽

Quantile Regression ◽

Public Assistance ◽

Medical Factors ◽

Quantile Regression Analysis

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Absenteeism and performance in a quantitative module A quantile regression analysis

Journal of Applied Research in Higher Education ◽

10.1108/jarhe-05-2014-0054 ◽

2016 ◽

Vol 8 (3) ◽

pp. 376-389 ◽

Cited By ~ 6

Author(s):

Pranab Kumar Pani ◽

Pallavi Kishore

Keyword(s):

Regression Analysis ◽

Academic Performance ◽

Learning Styles ◽

Quantile Regression ◽

United Arab Emirates ◽

Classroom Environment ◽

Negative Impact ◽

Content Type ◽

Quantile Regression Analysis ◽

And Performance

Purpose – There is growing evidence that learning is faster, measurably better and more productive in a classroom setting when a student attends classes regularly. Each student brings in his/her experience, skills, and unique learning styles to a class – thus a classroom environment can potentially create positive externalities through which a student can gain substantially from various strengths of his/her peers. However, students do remain absent from their classes for a variety of reasons. One of the measurable effects of regular non-attendance in a university class, where students from various cultures and regions interact, is the academic performance. The purpose of this paper is to determine if there is any potential causal link between absenteeism (attendance) and academic performance. Design/methodology/approach – Data were culled from the records of three batches of students in a British university campus in the Middle East. Quantile regression methods were used to establish the causal relationship between absenteeism and academic performance. Findings – A quantile regression analysis reveals that absenteeism has negative impact on academic performance. This also suggests that low performers are worse affected by absenteeism as compared to the high performers. Research limitations/implications – Inclusion of some other factors, such as study habits, additional hours spent on quantitative modules, student’s ethnicity background, particularly in the context of United Arab Emirates, could have emboldened the robustness of the study. Non-availability or paucity of this information, to some degree, has limited the conclusions of this study. Originality/value – Proponents of mandatory attendance argue that there is a positive correlation between attendance and performance. But, one very important issue which gets overlooked is who actually benefits more by attending classes – are the shirkers who have a poor attendance record or the ones who are more sincere, more regular, and active participants in a class? This study uses quantile regression analysis to address this issue.

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Climatic variability and thermal stress in Pakistan’s rice and wheat systems: A stochastic frontier and quantile regression analysis of economic efficiency

Ecological Indicators ◽

10.1016/j.ecolind.2017.12.014 ◽

2018 ◽

Vol 89 ◽

pp. 496-506 ◽

Cited By ~ 12

Author(s):

Muhammad Arshad ◽

T.S. Amjath-Babu ◽

Sreejith Aravindakshan ◽

Timothy J. Krupnik ◽

Verena Toussaint ◽

...

Keyword(s):

Regression Analysis ◽

Thermal Stress ◽

Quantile Regression ◽

Economic Efficiency ◽

Climatic Variability ◽

Stochastic Frontier ◽

Quantile Regression Analysis

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