scholarly journals Towards a comprehensive assessment system of local government fiscal health

2021 ◽  
Vol 95 (7/8) ◽  
pp. 233-244
Author(s):  
Jurriaan Kooij ◽  
Tom Groot
Keyword(s):  
Local Government ◽  
Prediction Models ◽  
Empirical Studies ◽  
Health Indicators ◽  
Service Level ◽  
Bankruptcy Prediction ◽  
Assessment System ◽  
Fiscal Health ◽  
Performance Dimensions

Understanding fiscal health, also commonly referred to as financial condition, is key to sound decision making and the proper functioning of local government. Nonetheless there is no agreed upon way to measure fiscal health. We argue that the use of a conceptual framework is essential in furthering our understanding of measuring and assessing local government fiscal health. In this study we offer a framework and a set of financial accounting indicators visualizing fiscal health on the short and long term, taking into account the existing liabilities and local government obligations towards its constituents. The study draws on the theoretical and empirical analysis of corporate bankruptcy prediction models and local government fiscal distress models. We develop a possible comprehensive set of fiscal health indicators and compare it with existing empirical studies of local government fiscal health. The model captures current performance in four solvency dimensions (cash, budget, service-level and long term) and allows for predictions of future performance, taking into account risks (predictors of possible future financial stress) and capabilities (opportunities to strengthen future financial health). We tested our model by reviewing 33 empirical studies and found that we could allocate all indicators used to the dimensions of our framework. No empirical study appears to address all dimensions. The selection of performance dimensions is partly driven by the studies’ research objectives.

Does intellectual capital help predict bankruptcy?

2018 ◽  
Vol 19 (2) ◽  
pp. 321-337 ◽  
Author(s):  
Velia Gabriella Cenciarelli ◽  
Giulio Greco ◽  
Marco Allegrini
Keyword(s):  
Performance Measures ◽  
Intellectual Capital ◽  
Financial Stability ◽  
Prediction Models ◽  
Predictive Ability ◽  
Time Frame ◽  
Bankruptcy Prediction ◽  
Superior Performance ◽  
Content Type

Purpose The purpose of this paper is to explore whether intellectual capital affects the probability that a particular firm will default. The authors also test whether including intellectual capital performance in bankruptcy prediction models improves their predictive ability. Design/methodology/approach Using a sample of US public companies from the period stretching from 1985 to 2015, the authors test whether intellectual capital performance reduces the probability of bankruptcy. The authors use the VAIC as an aggregate measure of corporate intellectual capital performance. Findings The findings show that the intellectual capital performance is negatively associated with the probability of default. The findings also indicate that the bankruptcy prediction models that include intellectual capital have a superior predictive ability over the standard models. Research limitations/implications This paper contributes to prior research on intellectual capital and firm performance. To the best of the knowledge, this is the first study to show that the benefits of intellectual capital extend from superior performance to long-term financial stability. The research can also contribute to bankruptcy studies. By using a time frame covering decades, the findings suggest that intellectual capital performance measures can be included in bankruptcy prediction models and can effectively complement traditional performance measures. Originality/value This paper highlights that intellectual capital is associated with long-term financial stability and a lower bankruptcy risk. Firms realising the potential of their intellectual capital can produce a virtuous circle between higher performance and greater financial stability.

scholarly journals Applications of Distress Prediction Models: What Have We Learned After 50 Years from the Z-Score Models?

2018 ◽  
Vol 6 (3) ◽  
pp. 70 ◽  
Author(s):  
Edward I. Altman
Keyword(s):  
Financial Distress ◽  
Prediction Models ◽  
Empirical Studies ◽  
Warning Signal ◽  
Bankruptcy Prediction ◽  
Z Score ◽  
Multivariate Statistical ◽  
Practical Applications ◽  
Multivariate Statistical Model ◽  
Credit Risk Measurement

Fifty years ago, I published the initial, classic version of the Z-score bankruptcy prediction models. This multivariate statistical model has remained perhaps the most well-known, and more importantly, most used technique for providing an early warning signal of firm financial distress by academics and practitioners on a global basis. It also has been used by scholars as a benchmark of credit risk measurement in countless empirical studies. Practical applications of the Altman Z-score model have also been numerous and can be divided into two main categories: (1) from an external analytical standpoint, and (2) from an internal to the distressed firm viewpoint. This paper discusses a number of applications from the former’s standpoint and in doing so, we hope, also provides a roadmap for extensions beyond those already identified.

scholarly journals Własny potencjał dochodowy gmin wiejskich w Poznańskim Obszarze Metropolitalnym

2017 ◽  
Vol 104 (4) ◽  
pp. 62-74
Author(s):  
Agnieszka Kozera
Keyword(s):  
Rural Communities ◽  
Local Government ◽  
Local Development ◽  
Empirical Studies ◽  
Data Bank ◽  
Financial Policy ◽  
Local Data ◽  
Central Statistical ◽  
Central Statistical Office

The analysis of the income situation of units of local self-government (entities of local government) based on achieved income, which include most of the sources of income of their own, can determine the long-term ability of these entities to finance their activities. Their own income potential allow local government units to create their own financial policy within the framework of existing law, so it is one of the important factors of sustainable local development. Among the communes, the lowest level of their own income potential distinguishes rural communes. However, these entities are highly diverse in this regard. With the socio-economic development, and especially after Poland’s accession to European structures, the functions performed by rural communes (from the typical agricultural to residential and service functions), and especially those located in the vicinity of the largest cities, are changing. Change of functions performed by rural communities, especially those located in the so-called. Metropolitan areas, translates into a change in the level and structure of their own income of these entities. The main aim of the paper is to analyze the level and structure of own income potential of rural communities in the Poznań Metropolitan Area in the years 2004-2016. Empirical studies were conducted based on data from the Local Data Bank of the Central Statistical Office, which were processed using basic descriptive statistics methods.

Is inflation targeting useful for economic growth?

2017 ◽  
pp. 62-74 ◽  
Author(s):  
P. Kartaev
Keyword(s):  
Economic Growth ◽  
Monetary Policy ◽  
Test Performance ◽  
Inflation Targeting ◽  
Developing Economies ◽  
Empirical Studies ◽  
Growth Regime ◽  
Potential Channels

The paper presents an overview of studies of the effects of inflation targeting on long-term economic growth. We analyze the potential channels of influence, as well as modern empirical studies that test performance of these channels. We compare the effects of different variants of inflation targeting (strict and mixed). Based on the analysis recommendations on the choice of optimal (in terms of stimulating long-term growth) regime of monetary policy in developed and developing economies are formulated.

Paradoxes of reservation wage setting in the Russian labor market. Part I

2016 ◽  
pp. 5-27
Author(s):  
R. Kapeliushnikov ◽  
A. Lukyanova
Keyword(s):  
Labor Market ◽  
Empirical Studies ◽  
Reservation Wage ◽  
Wage Setting ◽  
Reservation Wages ◽  
Monitoring Survey ◽  
Main Determinants ◽  
Subjective Estimates ◽  
Objective Indicators

Using panel data from the Russian Longitudinal Monitoring Survey for 2006-2014, the paper investigates reservation wages setting in the Russian labor market. The sample includes non-employed individuals wishing to get a job (both searchers and non-searchers). The first part of the paper provides a survey of previous empirical studies, describes data and analyzes subjective estimates of reservation wages in comparison with various objective indicators of actual wages. The analysis shows that wage aspirations of the majority of Russian non-employed individuals are overstated. However their wage expectations are rather flexible and decrease rapidly as the search continues that prevents high long-term unemployment. The second part of the paper provides an econometric analysis of main determinants of reservation wage and its impact on probability of re-employment and wages on searchers’ new jobs.

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 48-50
Author(s):  
Ana Isabel Velasco Fernández ◽  
◽  
Ricardo José Rejas Muslera ◽  
Juan Padilla Fernández-Vega ◽  
María Isabel Cepeda González
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Prediction Models ◽  
Bankruptcy Prediction ◽  
Artificial Neural

Forecasting Revenue Impacts from COVID-19: The Case of Florida Municipalities

2021 ◽  
pp. 0160323X2110120
Author(s):  
Hai (David) Guo ◽  
Can Chen
Keyword(s):  
Local Government ◽  
Short Term ◽  
Fiscal Planning ◽  
Revenue Structure ◽  
Municipal Managers ◽  
The Impact

Early in the pandemic, Florida municipal managers indicated that forecasting the impact on local revenues was one of their top priorities in responding to the pandemic, yet such a tool has not been widely available. This study offers simple and straightforward fiscal planning guides for assessing the short-term and long-term impacts of the COVID 19 recession on local government revenues by estimating the revenue declines among 411 Florida municipalities from FY 2021 to FY 2023. The forecast results predict revenues will be reduced by $5.11 billion from 2019 pre-pandemic levels for Florida cities in fiscal years 2021 through 2023. The decline is forecast to be 3.54 percent in FY 2021, 4.02 percent in FY 2022, and 3.29 percent in FY 2023. The revenue structure matters for estimating the revenue decline.

scholarly journals Wood creep data collection and unbiased parameter identification of compliance functions

Holzforschung ◽  
2020 ◽  
Vol 74 (11) ◽  
pp. 1011-1020
Author(s):  
Danyang Tong ◽  
Susan Alexis Brown ◽  
David Corr ◽  
Gianluca Cusatis
Keyword(s):  
Parameter Identification ◽  
Prediction Models ◽  
Tall Buildings ◽  
Building Design ◽  
Parameter Distribution ◽  
Experimental Conditions ◽  
Global Emission ◽  
Wood Construction ◽  
Parameter Values

AbstractRising global emission have led to a renewed popularity of timber in building design, including timber-concrete tall buildings up to 18 stories. In spite of this surge in wood construction, there remains a gap in understanding of long-term structural behavior, particularly wood creep. Unlike concrete, code prescriptions for wood design are lacking in robust estimates for structural shortening. Models for wood creep have become increasingly necessary due to the potential for unforeseen shortening, especially with respect to differential shortening. These effects can have serious impacts as timber building heights continue to grow. This study lays the groundwork for wood compliance prediction models for use in timber design. A thorough review of wood creep studies was conducted and viable experimental results were compiled into a database. Studies were chosen based on correlation of experimental conditions with a realistic building environment. An unbiased parameter identification method, originally applied to concrete prediction models, was used to fit multiple compliance functions to each data curve. Based on individual curve fittings, statistical analysis was performed to determine the best fit function and average parameter values for the collective database. A power law trend in wood creep, with lognormal parameter distribution, was confirmed by the results.

Sign in / Sign up

Export Citation Format

Share Document