The objective of this paper is to introduce and propose what we may refer to as pipe theory. A pipe usually refers to an elongated and cylindrical object with equally sized apertures at both ends. This would differentiate it from a funnel where the beak is much larger than the lower opening or aperture. As a matter of fact, we propose that equal size openings at both ends would represent equal chances of an object entering or exiting a piper ceteris paribus, and all other things being equal, and this would constitute the foundation of pipe theory. There may or may not be internal processes involved, though the latter would vary depending on the circumstances. In some cases, there could be intake and discharge or leakage in the middle, and segmental analysis can also be performed. Intake and discharged may be guaranteed or uncertain; they could also increase or decrease either based or not based on a contingency; i.e. contingent on some other event occurring or happening. Both static and diachronic analysis can be performed, and comparative statics used as well. This analysis can also be combined with cause and effect analysis, and compositional analysis among others, for greater efficacy. We also present a large number of examples such as population analysis, order pipelines, intake and outtake analysis, and the like. This paper can eventually become a springboard for more complex downstream analysis, both qualitative and quantitative, and must be according its pride of place in twenty-first century science, particularly in the social sciences.

The financial sector is central to any economy, as it is responsible for the mobilization and allocation of credit. In Nigeria, as in many developing nations, the banking sector is the most dominant part of the financial system. It is in light of the above that the study investigated the link between banking sector development and human development in Nigeria. The study utilized secondary data from 1981 to 2023, which was analyzed using an error correction model. The findings indicated a positive correlation at a 5% significance level between economic development, proxied by the Human Development Index (HDI), and banking sector development (PSC/GDP), aligning with theoretical expectations. Specifically, a 1% increase in the growth rate of PSC/GDP three years prior is associated with a 0.019% increase in the current growth rate of HDI, ceteris paribus, implying that improvements in the banking sector contribute positively to economic development. Conversely, gross domestic investment as a proportion of gross domestic product (GDI/GDP) demonstrated a significant lagged negative impact on economic development (HDI). Consequently, the study recommended that monetary authorities in Nigeria should implement policy measures to enhance investment in areas that foster human capital development, ultimately leading to increased economic development.

BackgroundThe Cox proportional hazards (CPH) model is a common choice for analyzing time-to-treatment interruptions in patients on antiretroviral therapy (ART), valued for its straightforward interpretability and flexibility in handling time-dependent covariates. Machine learning (ML) models have increasingly been adapted for handling temporal data, with added advantages of handling complex, nonlinear relationships and large datasets, and providing clear practical interpretations.ObjectiveThis study aims to compare the predictive performance of the traditional CPH model and ML models in predicting treatment interruptions among patients on ART, while also providing both global and individual-level explanations to support personalized, data-driven interventions for improving treatment retention.MethodsUsing data from 621,115 patients who started ART between 2017 and 2023, in Kenya, we compared the performance of the CPH with the following ML models—gradient boosting machine, extreme gradient boosting, regularized generalized linear models (Ridge, Lasso, and Elastic-Net), and recursive partitioning—in predicting first and multiple treatment interruptions. Explainable surrogate technique (model-agnostic) was applied to interpret the best performing model’s predictions globally, using variable importance and partial dependence profiles, and at individual level, using breakdown additive, Shapley Additive Explanations, and ceteris paribus.ResultsThe recursive partitioning model achieved the best performance with a predictive concordance index score of 0.81 for first treatment interruptions and 0.89 for multiple interruptions, outperforming the CPH model, which scored 0.78 and 0.87 for the same scenarios, respectively. Recursive partitioning’s performance can be attributed to its ability to model nonlinear relationships and automatically detect complex interactions. The global model-agnostic explanations aligned closely with the interpretations offered by hazard ratios in the CPH model, while offering additional insights into the impact of specific features on the model’s predictions. The breakdown additive and Shapley Additive Explanations explainers demonstrated how different variables contribute to the predicted risk at the individual patient level. The ceteris paribus profiles further explored the time-varying model to illustrate how changes in a patient’s covariates over time could impact their predicted risk of treatment interruption.ConclusionsOur results highlight the superior predictive performance of ML models and their ability to provide patient-specific risk predictions and insights that can support targeted interventions to reduce treatment interruptions in ART care.

The impairment argument aims to establish the immorality of abortion without relying on the fetus's moral status. Instead, it appeals to logical consistency in moral reasoning: if it is immoral to impair a fetus by causing injury, then it must be even more immoral to impair it by causing death. For this reasoning to succeed, all the morally relevant details between these impairments must be held constant, which the author of the argument, Perry Hendricks, refers to as the ceteris paribus requirement. This requirement has proven difficult to define, and in his latest work, Hendricks suggests a more precise explanation of the ceteris paribus clause based on the valuable goods that obtain from impairments. He also outlines a test to determine if the ceteris paribus clause is broken, thereby causing the impairment argument to fail. In this paper, I argue that this new formulation is too narrow, resulting in fatal counterexamples. Accordingly, I show that in addition to valuable goods, the harms of impairment must be considered, as well as the reasons why impairing a fetus is considered immoral. I demonstrate that these reasons ultimately rest on one's view of the fetus' moral status, rendering the impairment argument superfluous.

Agriculture refers to the science, art or practice of cultivating the soil and growing crops. Government spending and institutional credit are the most important factors that engender agricultural innovation and rural income security for over 50% of India’s population who derive their livelihood directly from farming. This paper assesses the role of agricultural expenditure by the government, access to formal credit and its role in supporting livelihood in agricultural regions. Government consumption includes outlays on infrastructure, subsidies, and financial programs to enhance gains realized from agricultural production. Institutional credit on the other hand, comprises the formal sources of funds including bank credit, cooperative credit and microfinance made available to farmers for purchase of necessary inputs and as hedge to output risk. This study, therefore, adopts a secondary data research strategy supplemented by case studies to establish the impact of these financial tools on the stability and income of farming households. These findings thus reveal the major challenges facing extension of government policies and of credit schemes, with a large number of such S&MF remaining outside the coverage. The study also highlights the influential parameters like spatial distribution, financial literacy and institutional mechanisms that intervene with the relationship between government spending, credit availability and sustenance. The study also finds a strong correlation between government expenditure, income and farmer suicides, where ceteris paribus, 8.788 unit decrease in government spending leads to one unit increase in farmer suicides and ceteris paribus, 9.517 unit increase in government spending leads to one unit increase in income. Therefore, with these findings the paper provides policy implications on resource management in delivering credit and rural employment for betterment of the people and sustainability of agriculture in the overall context of India.

Purpose: Design scientists, philosophers of science, and project designers hold mixed views on evaluating participatory design research, projects, processes, and outcomes. We argue that design science research produces varied contributions, including theories, methods, and artefacts. From a critical realist perspective, evaluation emphasizes mechanisms-based explanations. This paper examines the role of mechanisms in design science research and shows how studying them enhances statistical approaches for causal inference. It distinguishes statistical from causal inference; discusses mechanisms and mechanism-based explanations; mechanism quantification; mechanisms in explaining individual actions; and mechanisms in explaining outcomes. Drawing lessons from an empathetic participatory design process, it illustrates how design science studies can be situated within critical realism. Materials and Methods: This study adopts design science research, combining qualitative and quantitative approaches. It includes an extensive literature review and uses empirical statistical data from mechanisms observed in participatory design processes involving prototyped citizen incident reporting applications. Data collection employed qualitative repertory grids with potential citizen users; constructs were then incorporated into a quantitative structured questionnaire for empathetic prototype testing with designers. Prototype evaluation follows the Realist Evaluation model of Context-Mechanism-Outcome Configuration (CMOc), which explains how and why interventions work by analyzing Contexts (conditions), Mechanisms (activated forces), and Outcomes (intended or unintended results). Findings: Inferentially, co-designed artifact features show a causal-mechanism relationship to perception (sig.=0.397) and projection (sig.=0.222), but not to understanding (sig.=0.177). Significant causal interrelationships exist among situation awareness constructs. There are also significant relationships between perception and action (sig.=0.382), comprehension and action (sig.=0.312), and projection and action (sig.=0.450). Relationships involving situation awareness constructs, PAL, and e-government artifact adoption were not tested. Implications to Theory, Practice and Policy: Informed by Personal Constructs Theory (PCT) and Situational Awareness, which view individuals as scientists forming bipolar mental frameworks to interpret and predict the world. The paper advances debates on rigor and relevance in design science research, arguing that a critical realist lens balances rigor (via statistical inference) and relevance (via problem-solving prototypes). Researchers may treat context variables as explicit or implicit ceteris paribus conditions and explore additional causal relationships based on design and evaluation contexts.

This paper examines, through a modified aggregate demand curve, the reduction in equilibrium income caused by the presence of precautionary demand in the money demand function. Specifically, this paper rigorously analyses the transformation of the well-known fiscal and monetary policy multipliers, β and γ, commonly found in macroeconomic theory textbooks. Ceteris paribus, an increase (decrease) in precautionary money demand reduces (increases) equilibrium income, as can be seen through the modified multipliers β and γ. Multiple contingencies that emerged suddenly between 2008 and 2023 may have altered agents’ perceptions regarding precautionary money demand. This work contributes to the adaptation of some well-established tools of macroeconomic theory to address events of this nature.

While Marshall’s views on the method of economics are familiar, Allyn Young’s views on the subject have escaped attention in the literature. This article, by situating Young’s ideas in comparison with Marshall’s, tries to fill an important lacuna in the literature. Both admired classical political economy and the German historical school. Both, in some ways, felt that it was not the concrete truths but the engine for the discovery of concrete truths that was more important. While both had broadly similar views on the method, Young was an original thinker in his own right. Particularly, he rejected Marshall’s partial equilibrium approach in favor of a disequilibrium approach to economics. He felt that Marshall’s supply-demand curves hold ceteris paribus and cannot be integrated to give a good social picture. He viewed the economic phenomenon in its togetherness, but this togetherness did not lead to equilibrium but disequilibrium. Finally, both were evolutionary economists, and their comparison would be of interest to an institutional journal.

We quantify the effect of biannual time changes on sentiment using US online and social media posts from periods around changes to Daylight Saving Time (DST) in the spring and Standard Time (ST) in the fall over the period 2019-2023. We compare sentiment-a measure of individuals overall mood or emotions towards an event-in cities on either side of US time zones the day before and after the societal time change. We find negative shocks to sentiment following both time changes. This effect seems stronger in the fall. Given the amount of daylight relative to a fixed work schedule should be the same in each group of cities on these days, these differences suggest strong negative ceteris paribus reactions to societal time changes, which may indicate preference to abolish these adjustments, although we do not measure preference for DST versus ST. We also use regression analysis to estimate how sentiment changes over time. We find persistent negative impacts from the change to Standard Time in the fall. In contrast, individuals experience a noisy shock to sentiment that attenuates over time. These findings provide evidence that individuals have a more negative reaction to the societal time change to Standard Time in the fall than they do to DST in the Spring. This work highlights the potential that the reaction to societal time changes varies depending on whether moving to or away from DST or Standard Time.

This study empirically examined the economic burden of ill-health and the pathway of negative consequences of ill-health disability on small-holder agricultural households’ welfare (income and food spending) in Nigeria. The Nigeria’s Living Standard Measurement Study - Integrated Survey on Agriculture panel data (2010/11, 2012/13 and 2015/16) were used. Data analysis tools were descriptive statistics, cost of illness approach, and panel data instrumental variable regression model. Agricultural households whose members experienced ill-health disability had high direct and indirect costs of ill-health, with negative welfare consequences on the affected households. Direct costs included the Out of Pocket (OOP) healthcare and other related costs; indirect cost was the cost of lost productive time to the households. The proportion of indirect cost to the average total cost of ill-health was 65%. As a proportion of households’ income, estimates of direct cost was about 19%, and indirect cost was 39%. Results revealed that the pathway by which the burden of ill-health disability affected households’ welfare is through increased OOP healthcare expenditure and reduction in food budget. This study recommended the expansion of government-funded healthcare insurance to cover small-holder agricultural households and protect them from the direct and indirect burden of ill-health. Recognizing that findings are ceteris paribus, other complementary health financing efforts through the private sector, community-based initiatives and non-profit organizations in form of grants, loans and/or health related social corporate responsibility services are advocated to reduce productive days lost to ill-health and OOP payments which undermine agricultural production and household welfare.

Abstract We use the Mirrlees income tax model with migration between two countries to investigate the optimal labour income taxation of top earners, where individuals vary in skill levels and migration costs. We consider three scenarios of relative consumption concerns: comparisons with average consumption in the population, upward comparisons and comparisons with median‐skill individuals. The tax formulas for the optimal marginal tax rate imposed on top skills are derived in closed form. Ceteris paribus, the optimal tax rate decreases with the migration elasticity of top earners but increases with the degree of inequality or the intensity of relative concerns. To explore the joint impact of these factors on the optimal tax rate, we find that even when governments prioritize the most redistributive social objective (maxi‐min), an increase in the migration elasticity of top earners weakens the demand for reducing inequality, leading to a situation where the retention and attraction of top talent take precedence over inequality mitigation. Conversely, an increase in the migration elasticity of these individuals enhances the demand for correcting positional externalities. The quantitative significance of these theoretical findings is supported by numerical examples based on parameter estimates from empirical studies.

Economics is currently facing a crisis, influenced by the Neoclassical Synthesis and its welfare state model, as evidenced both in real-life situations and classroom settings. The study of mainstream economics relies heavily on formal reductionism and instrumentalism, which introduce biases such as the ceteris paribus axiom, ergodicity, ancilla statistica, and concepts like F-twist or mathiness. Additionally, mainstream economics has shown a lack of adaptation to social reality changes, including digitalization and globalization 2.0, as well as phenomena like permacrisis and polycrisis. The purpose of this work is to propose a heterodox mainline approach for renewing economics studies and their learning processes in a digital and practical manner. The methodology is based on heterodox theoretical and methodological frameworks, offering a critical review and systematization of biases and failures within current curricula and syllabi. The aim is to implement active learning experiences that incorporate digital literacy with real data, thereby enhancing the study of economics and reconnecting the subject with students and their future professional expertise. The results indicate that, through this proposed learning experience utilizing platforms with real data and heterodox analysis student participation and understanding have improved over three years at Rey Juan Carlos University. Furthermore, this approach provides a foundational framework that other educators in different institutions can adopt to replicate and adapt the experience effectively.

Floating interest Central Bank Digital Currency (CBDC) is a moderately risky financial asset. Given the risks involved and the returns attached, a rational investor has to determine the optimal allocation of wealth to the CBDC in his or her portfolio. The paper sought to establish the optimal wealth allocation to a floating interest rate CBDC and a risk-free asset. The study adopted an analytical design to illustrate the theoretical optimal holding of floating interest rate CBDC by individual investors based on Merton's 1969 mathematical model. Using data collected from the Central Bank of Kenya and Kenya National Bureau of Statistics, the paper applied the Merton model to a hypothetical proxy for CBDC, and real-world data on inflation, interest, and 91-day T-bill, to allocate investors' wealth to floating interest CBDC and a risk-free asset. The results show that optimal wealth allocation to floating interest rate CBDC was a function of the risk premium, the degree of investor risk aversion and the volatility of the floating interest rate CBDC. The results further demonstrate that whenever CBDC offered a higher interest rate than a risk-free asset, investors would shift wealth to CBDC and vice versa. Further, whenever the volatility on CBDC returns increased, investors tended to hold fewer units of interest-bearing CBDCs and more of risk-free assets and vice versa. The optimal monthly consumption for the risk-averse investor was a function of subjective discounting rate, degree of investor risk aversion and previous wealth. A higher subjective discounting rate or a higher cumulative wealth, or a lower risk aversion was associated with increased optimal consumption, <i>ceteris paribus</i>, and vice versa is true. Our results therefore suggest that financial markets investment portfolios are sensitive to CBDC volatility, and this that can originate another strand of CBDCs literature. These findings provide useful insights to individual and institutional investors, and can guide policymakers and financial market regulators on the important link between CBDC and financial markets in the new digital-currency era. For example, policymakers and regulators can adjust fiscal and monetary policy by considering the possible impact on investor portfolios. This can guide investors to strategically adjust their portfolio positions.

ABSTRACT The present study investigates the optimal integrated greenhouse gas emission abatement strategy for the forest and energy sectors. To this end, a cross-sectoral modelling approach is employed, utilizing two sectoral models and applying them to the case of Hungary. The Forest Carbon Sink Optimization Model (FOX) provides information regarding the additional carbon sequestration in the forest sector and the forest fuelwood harvest induced by policy instrument under different carbon price cases. These outputs are then used as inputs to the HU-TIMES energy sector model to determine the remaining greenhouse gas (GHG) abatement target and the available fuelwood capacity for the energy sector. This enables the study of the impact of the relaxation of GHG abatement targets and a decline in the supply of primary solid biomass on the energy sector, under the assumption of ceteris paribus zero national net GHG emission in 2050. The findings suggest that the marginal abatement cost (MAC) of forest carbon offsets is notably lower than the MAC of numerous technologies in the compliance – energy – market. In the analyzed Hungarian case we find that the integrated compliance-offset design redirects over one-third of the necessary abatement from the energy to the forest sector. Consequently, an inverse relationship is observed between the carbon offset price and the total aggregated system cost, thus the socially cost-efficient climate strategy will require the promotion of additional carbon sequestration in forests potentially through carbon pricing. The findings of this study demonstrate notable robustness, even when considering the zero-emission factor attributed to biomass combustion and complete sequestration as part of biomass energy with carbon capture and storage.

Abstract The article offers an internal critique of Fodor’s original argument against the unity of science, claiming that multiple realization in special sciences blocks reduction to physical science and secures their autonomy. Fodor’s argument has been a cornerstone of the argument against reductionism in the philosophy of mind. In this article, we aim to show that it fails even when Fodor’s own presuppositions and his own understandings of key terms are considered. In this sense, the article probes the original argument for its internal consistency. Firstly, we provide an overview of multiple realization, along with the main motivation for it, i.e., the rejection of psychophysical reductionism, and a detailed discussion of Fodor’s claims and key terminology. This is followed by examining Fodor’s argument against psychophysical reductionism using his key example of multiple realization, Gresham’s law in economics. We argue that the law is either not multiply realized or basic sciences are also multiply realized, both options being problematic for Fodor. Turning to the apparent impossibility of reducing ceteris paribus special science laws via exceptionless bridge laws to exceptionless physical laws, we argue that the problem lies in the notion of “proper law”: if understood as an exceptionless law, the argument rests on a contradiction, and if understood as a “not gerrymandered” (not arbitrary) law, the key assumption of the argument, i.e., that special science kinds are natural, is simply false. The original argument, therefore, fails to establish the autonomy of special sciences even if Fodor’s own understanding of key terms is adopted, which leaves him, contrary to his opinion, empty-handed in the battle against psychophysical reductionism.

This study examines Ghana's annual household food expenditures and their Engel food curve using the latest data from the 2017-2018 seventh round of the Ghana Living Standards Survey, which covered 14,009 household and lasted for one-year. Household demographics and specific variables influencing annual household food budget decisions in Ghana were examined, including income, household size, educational status of household head, household location, and household connectivity to electricity. The study establishes an inverse relationship between the share of the household food budget and the increase in household income, and a high annual household food expenditure elasticity with 0.49 pesewas out of every one cedi serving as an annual household marginal food budget share in Ghana, on average and <i>ceteris paribus</i>. The study provides additional statistical evidence that characterizes food as a necessity in Ghana and placed the country in the medium food insecurity zone. Economic development in Ghana means achieving food security at all times, which calls on the country to redouble its efforts to meet SDG Goal 2 and the AU Agenda 2063 household food security targets.

Artificial intelligence or AI is reshaping the U.S. economy; On one hand, it is improving potential for productivity and innovation, but on the other side it raises concerns about inequality. This paper investigates how AI-driven automation impacts income disparities across race, gender, and nativity. In the methodology of this paper, by using microdata from the ACS (American Community Survey), evaluating the regression analysis of log income, ceteris paribus, where demographic and contextual factors are controlled while AI exposure is interacted with key social categories. The analysis results in a tendency that higher AI exposure is associated with income, and that AI-intensive sectors yield an advantaged 0.0619 increase in log income. But the uneven distribution of benefits in gender, race, and nativity remains an issue, Specifically, there is a widening gender wage gap from the extra gain from men comparing to women, non-Blacks individuals earn 0.0286 log income more than Black workers, widening the racial wage gap by 9.4%, native individuals in the country has greater access to AI complementary employments, resulting a reduced log income gap by 35.8% comparing to non-natives. This is evidence that AI has the ability to reshape and reinforce inequality, and policies such as training or AI-targeting taxation should be counterpointed to ensure that AI automation promotes inclusion rather than deepening systematic disparities.

Evaluating management effectiveness is critically important as it enables targeted decision-making, such as reshuffling management teams or scaling successful practices, which underscores the relevance of this research. The study aims to develop an economic-mathematical toolkit for assessing regional-level management effectiveness across the subjects (regions) of the Russian Federation. This assessment focuses on a designated indicator of socio-economic development, holding other factors constant (ceteris paribus), using the following exemplar indicators: total fertility rate, life expectancy, and mortality from cardiovascular diseases. According to the research hypotheses, estimates of management effectiveness derived using regional fixed effects will differ from those based on the direct ranking of observable statistical indicators. Furthermore, these estimates are hypothesized to display varying degrees of robustness when analyzed across different model specifications. The research procedure was implemented by isolating the influence of factors unrelated to specific managerial actions from observable objective statistical indicators. This isolation was achieved through the estimation of regional fixed effects using various models based on panel data and spatial econometrics techniques. The results confirm the research hypotheses. The developed methodology enables the construction of regional rankings for the target indicator with minimal data input requirements, and tools for assessing the reliability/confidence level of the resulting rankings. Furthermore, the methodology offers tools for for the generation of composite rankings based on a group of indicators, weighted using estimates of the value of statistical life within the context of the respective indicators. The theoretical significance of the findings lies in advancing approaches to modeling management effectiveness through the isolation of regional fixed effects. These effects are purged of the influence of local socio-economic, demographic, and other territorial characteristics, as well as the spillover effects from neighboring regions (spatial dependence). Practically, the study enahances the precision of approaches for evaluating the effectiveness of managerial interventions. Specifically, it improves the capability to account for the linkages between specific decisions made by managers and their resulting position in the performance rankings.

This study investigates the transformative potential of the African Continental Free Trade Area (AfCFTA) in reshaping intra-African trade dynamics. Employing a gravity model approach, the research elucidates the complex trade relationships intrinsic to the African continent, highlighting the opportunities and growth prospects AfCFTA presents for economic advancement, trade efficiency enhancement and regional integration promotion. To conduct this analysis, panel data were sourced from diverse data sources, including the CEPII Data, the International Monetary Fund, the World Integrated Trade Solution (WITS), the Worldwide Governance Indicators (WGI) and the World Development Indicators. The ordinary least squares (OLS) regression results reveal a notable positive correlation between the AfCFTA and intra-African trade, suggesting a potential increase of 52.3% in intra-African trade attributable to the AfCFTA. The findings further delineate significant disparities in gross domestic product (GDP) among member nations, thereby underscoring the existing economic imbalances within the trade area. The results indicate that for every percentage increase in GDP, intra-African trade has a 50% likelihood of experiencing an uptick. Conversely, a percentage increase in distance yields an average decrease of 8.9% in intra-African trade, all other factors remaining constant ( ceteris paribus ). The model demonstrates a strong fit, with the independent variables accounting for 89.3% of the variance in the dependent variable. Additionally, the fixed effects analysis corroborates that the AfCFTA exhibits a positive and statistically significant relationship with intra-African trade at the 10% level, although indicating a weaker association quantified at 35.2%. The analysis further reveals that trade increases by $0.485 for every unit dollar increase in GDP. The Poisson pseudo-maximum likelihood (PPML) results affirm the model’s robustness, demonstrating that independent variables elucidate 90.4% of the variance in the dependent variable. Moreover, a percentage increase in the AfCFTA correlates with a 37.5% increase in trade. Instrumental variables techniques were also employed to correct for potential endogeneity, particularly with GDP and distance, confirming the reliability and robustness of the estimated coefficients. The study also emphasizes the alignment of the AfCFTA with the Sustainable Development Goals, particularly concerning poverty alleviation and the enhancement of economic opportunities. However, it is noteworthy that being landlocked negatively impacts trade between nations. Geographically, nations in closer proximity tend to engage in higher volumes of trade, while those situated further apart experience impediments to trade.

The issue of the quality of public finances is gaining importance in light of long-term fiscal sustainability challenges. The Recovery and Resilience Facility (RRF) can play a role in improving the quality of public finances by reshaping the composition of general government expenditure by function and supporting the economy’s long-term growth potential. This paper analyses the validity of Wagner’s law for Euro area countries and examines the evidence on the quality of public finances based on productive government expenditure. The quantitative approach is based on panel data approaches. The results do not confirm the validity of Wagner’s law. However, they indicate that the RRF, as an instrument of exogeneous fiscal intervention, has contributed to a shift in the composition of government expenditure, thereby providing some evidence of an improvement in the quality of public finances. Given that the RRF is a temporary, performance-based programme, it represents—at best—a temporary form of exogeneous fiscal intervention on the quality of public finances, which, upon its completion and ceteris paribus, will remain within the domain of the Member States.