Search results

This paper aims to weigh the restrictions to job creation imposed by labor market imperfections with respect to financial market imperfections. The authors want to see which restriction is more severe, and thus assess which is more powerful in creating permanent employment if it were removed.

A structural estimation is performed. The policy rules of the dynamic programming model are integrated into a simulated maximum likelihood procedure by which the model parameters are recovered. Data come from the CBBE (Balance Sheet data from the Bank of Spain). Identification of key parameters comes mainly from the observation of debt variation and sluggish adjustment to permanent labor.

Long-run permanent employment increases up to 69% when financial constraints are removed, whereas permanent employment only increases up to 54% when employment protection or firing costs are eliminated. The main finding of this paper is that the long-run expansion of permanent employment is larger when financial imperfections are removed than when firing costs are removed, even when there are important wage increases that moderate these employment expansions.

The removal of firing costs has been suggested by several economists as a result of the analysis of labor market imperfections. These policies, however, face the strong opposition of labor unions. This paper shows that the goals of permanent job creation can be accomplished without removing employment protection but by means of enhancing financial access to firms.

The connection between financial constraints and employment has been studied in recent years, motivated by the Great Recession. However, there is no assessment of how financial and labor market imperfections compare with each other to restrict permanent job creation. This comparison is crucial for policy analysis. This study is an attempt to fill out this gap in the economic literature. No previous research has attempted to perform this very important comparison.

The present paper aims to evaluate the structural impact of exogenously induced fiscal shocks on the Moroccan economy. This entails an analysis of the effect on the GDP of COVID-19-induced fiscal shocks manifesting in terms of budgetary revenues and expenditures. A key aspect of this analysis addresses the size of the tax and fiscal multipliers.

The study examines the structural relationship between five variables during the period between Q1 2009 and Q2 2020 using an SVAR approach that allows for a dynamic interaction between ordinary expenditures and revenues on a quarterly basis.

Positive structural shocks on public spending are likely to negatively impact economic growth. Negative economic growth, in turn, will damage price levels and interest rates, mainly over the long term. However, public-revenue-multiplier-associated shocks exceed these price- and interest-rate multiplier-associated shocks. Indeed, a structural shock to ordinary revenues can have a positive but insignificant impact on the GDP stemming from the ensuing decrease in the government budget deficit that proceeds from the increase in government revenues.

This is one of the first studies in the Moroccan context to assess the impact of the current worldwide pandemic on public finances. In addition, this study highlights the importance of boosting economic recovery through public spending.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.