scholarly journals The Impact of Training on Productivity and Wages - Evidence from Belgian Firm Level Panel Data

2008 ◽  
Author(s):  
Jozef Konings
Keyword(s):  
Panel Data ◽  
Firm Level ◽  
The Impact

scholarly journals Exploring the Relationship between Financial Distress, Financial Flexibility, and Firm Performance: Empirical Evidence from Pakistan Stock Exchange

2018 ◽  
pp. 1-16
Author(s):  
Yasin Mahmood ◽  
Muhammad Faisal Rizwan ◽  
Abdul Rashid
Keyword(s):  
Firm Performance ◽  
Panel Data ◽  
Financial Distress ◽  
Stock Exchange ◽  
Z Score ◽  
Firm Level ◽  
Financial Flexibility ◽  
Corporate Managers ◽  
And Performance ◽  
The Impact

Purpose– This main purpose of this paper is to empirically investigate the impact of corporate financial flexibility (FF) on financial distress and performance of firms listed on the Pakistan Stock Exchange (PSX). It enables to know how financial flexibility affects the firm financial strength, financial distress, and corporate performance. Design/methodology/approach –This study focuses on a firm level data of 192 non-financial firms covering the period 1992 - 2014. The fixed effect model logistic regression is applied by using unbalanced panel data to examine the impact of financial flexibility on financial distress, and performance of sample firms. Findings – The results reveal that financially flexible firms are less likely to face financial distress. As firms have more financial flexibility, the probability of financial distress decreases as well. It is also found that financially flexible firms are more likely to perform well than counterpart firms. By using the Altman z score as a measure of financial distress it is revealed that as the Altman z score increases, the chances of financial distress reduce as well. These findings also suggest the existence of pecking order in Pakistani firms; because firms rely on internal sources first, second go to external sources of financing. Practical implications – the findings of this study enable the corporate managers to avoid financial distress by obtaining and maintaining financial flexibility by keeping the leverage level lower than industry level. By attaining and maintaining financial flexibility, corporate managers can also raise the performance of the firm as well. It can also enable to make appropriate capital structure decision to finance managers of corporate firms. The creditors may provide the loan to sound firms who have no or least chances of financial distress. The lenders may also get benefit from it by requiring the interest rate as per risk of financial distress of the firm. Investors may avoid investing in firms having very little or no financial flexibility. JEL Classification– G33, L25 Keywords: Altman z score, financial flexibility, firm performance, return on asset, panel data, financial distress, modified z score.

scholarly journals Explaining leaving union membership by the degree of labour market attachment: Exploring the case of Germany

2015 ◽  
Vol 39 (1) ◽  
pp. 64-86 ◽  
Author(s):  
Janine Leschke ◽  
Kurt Vandaele
Keyword(s):  
Panel Data ◽  
Labour Market ◽  
Union Membership ◽  
Trade Unions ◽  
Firm Level ◽  
Non Union ◽  
The Impact

By particularly stressing the weaker labour market attachment of workers with non-standard contracts, this article contributes to the rather unexplored issue of mainly non-union-related reasons for leaving trade unions. Germany has been selected as a case study because German unions experienced a steady decline in membership, while at the same time non-standard employment arrangements increased considerably and more so than the European average. Using the German Socio-Economic Panel data, the authors construct a labour market attachment variable capturing different degrees of attachment. Their analysis shows the impact of labour market attachment and firm-level characteristics on union leaving and points especially to important differences across gender.

scholarly journals Does Financial Leverage Influence Investment Decisions? The Case Of Mauritian Firms

2011 ◽  
Vol 4 (9) ◽  
pp. 49 ◽  
Author(s):  
Mohun Prasadsing Odit ◽  
Hemant B. Chittoo
Keyword(s):  
Panel Data ◽  
Stock Exchange ◽  
Negative Relationship ◽  
Investment Decisions ◽  
High Growth ◽  
Financial Leverage ◽  
Firm Level ◽  
Data Set ◽  
Growth Firms ◽  
The Impact

This paper primarily focuses on the impact of financial leverage on investment decisions of firms and it is an attempt to explore the impact of financial leverage on investment levels using firm-level panel data in Mauritius. We expect to contribute to the existing literature by bringing evidence from a panel data set, which comprises 27firms, all listed on the Stock Exchange of Mauritius (SEM), sampled over a 15 year-period (i.e. from 1990 to 2004). In addition, we demarcate between two types of firms, namely: (i) high-growth firms; and (ii) low-growth firms. The results reveal a significant negative relationship between leverage and investment. More interestingly, while we found a negative relationship between leverage and investment for low growth firm, our econometric results reveal an insignificant relationship between the two variables for high growth firm.

Retrospective analysis of the resilience of Russian regions as socio-economic systems

2019 ◽  
pp. 46-64 ◽  
Author(s):  
Vladimir V. Klimanov ◽  
Sofiya М. Kazakova ◽  
Anna A. Mikhaylova
Keyword(s):  
Panel Data ◽  
Economic Systems ◽  
Financial Indicators ◽  
Russian Regions ◽  
Integral Index ◽  
Negative Effects ◽  
Economic Resilience ◽  
Correlation Dependence ◽  
The Impact ◽  
The Relationship

The article examines the impact of various socio-economic and financial indicators on the resilience of Russian regions. For each region, the integral index of resilience is calculated, and its correlation dependence with the selected indicators is revealed. The study confirms the relationship between fiscal resilience and socio-economic resilience of the regions. The analysis of panel data for 75 regions from 2007 to 2016 shows that there are significant differences in the dynamics of indicators in different periods. In particular, the degree of exposure to the negative effects of the crises of 2008—2009 and 2014—2015 in non-resilient regions is higher than in resilient ones.

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