This study analyses the effects of piped water on household food consumption per capita by adopting inverse-probability-weighted regression adjustment and endogenous treatment effects approaches with data from the Cambodia Socio-Economic Survey carried out in 2013 and 2017. A complementary analysis of the effects on primary household income per working-age member is also conducted to give insights into the potential consequences. The study also conducts a robustness check by estimating the fixed effects of piped water utilising village panel data. The results suggest that households using piped water are likely to enjoy higher food consumption per capita, with a complementary finding demonstrating that the use of piped water is likely to increase household income per working-age member.

Regulation of financial institutions has two key purposes: Solvency (prudential regulation) and consumer protection. Prudential regulation is implemented mainly by capital requirements, but governments also provide insurance for customer deposits, as a backup tool. In this article, we discuss the critical conditions for deposit insurance and capitalization to act as substitutes for each other, under cyclical economic environment. We make two assumptions. The first one is that deposit insurance is fairly priced and there is no moral hazard. The second one is that insurance creates incentives for moral hazard among insured banks, resulting in increased risk taking. We also discuss the critical conditions for deposit insurance and capitalization to be complementary under different proportions of deposit insurance.

This study focuses on the impact of trade in environmental goods (green trade) on the environment. We found that green trade can decrease pollution levels by exploiting a panel of 277 Chinese cities from 2004 to 2013 and using the instrumental variable (IV) strategy. However, total trade openness is far less favorable to the environment. We also found that both green imports and exports are conducive to the Chinese environment, while ordinary green trade performs better than green processing trade. Nevertheless, the effects of green trade are restricted by a city's purchasing power and absorptive capacity, as well as the classifications of environmental goods. Furthermore, green trade mainly promotes local green technological progress to benefit the environment.

This study explores the cause and effect of endogenous risk aversion in land pricing, where state intervention through taxation remains a general practice. Using a consumption-based asset pricing model incorporating taxation, it is shown that high taxation, due to the indexation effect, supporting land prices and reducing individuals' risk expectations, could lead to an endogenous decrease in risk aversion, which could result in market dysfunction because risk aversion plays a key role in the market mechanism. China, with its wholly state-owned land and the general use of land sales to cover financial deficits, is a typical case for empirical tests. The tests confirm that there, the rise in land prices was driven by the increase in reserve prices set by local governments, a strong means of taxation, and not by the market, indicating the endogenous decrease in risk aversion.

Skateparks, often called 'wheel parks,' are becoming increasingly common within communities worldwide. Despite this growth in parks, estimates show that the development of parks needs to catch up to users. Using a count data travel cost model, we estimate the adult user benefits associated with the Lauridsen Skatepark in Des Moines, Iowa – the largest in the United States. We estimate adult user benefits to be $61 per user per day and roughly $488,000 annually. This work contributes to the literature by being the first study to use econometric techniques to estimate skatepark user benefits. Second, we develop a simple and easy-to-apply method to assist municipalities in determining community skatepark needs. Third, our results support the literature showing that skateboarders are increasingly diverse.

This paper presents an operational framework for assessing the trajectories of production, energy, emissions, and capital accumulation to ensure the implementation of Nationally Determined Contributions (NDCs). The framework combines widely used methodologies (STIRPAT, system dynamics, and optimization) to simulate the pathways of variables until a target year. The CO-STIRPAT dynamic system allows us to identify the spillover pathways from carbon policy to economic growth based on output optimization principles; to conduct a more systematic analysis of the interconnections between the main drivers that determine carbon emissions; to develop a cost-effective climate policy mix that is a backbone for the right combination of carbon pricing, energy efficiency, and carbon intensity; and to assess NDC targets with respect to ambition gaps, implementation gaps, and feasibility.

In this paper I will show that budget deficit (or fiscal deficit) is necessary to achieve full employment under constant prices or inflation, using a model of endogenous growth in which consumers hold money for the reason of liquidity and live forever. Budget deficit need not be offset by future budget surpluses. I consider the continuous time case by taking the limit of the discrete time case when the time interval approaches zero. A continuous time dynamic model seems to be more general than a discrete time model. When the actual budget deficit is greater (smaller) than the value which is necessary and sufficient for full employment under constant prices, an inflation (a recession) occurs. The main argument of this paper is that a growing economy requires the continuation of budget deficit, and that we should not think of paying off the resulting government debt with taxes.

We study analytically the conflict of goals between stabilizing economic activity and public debt sustainability, for the fiscal authorities. In the short run, an active and expansionary fiscal policy, increasing public investment or reducing the labor taxation rate, is growth enhancing. However, as these short term fiscal policies also decrease government revenue and increase the public debt, budgetary and fiscal multipliers are reduced in the long run. In the framework of a potential ZLB constraint for monetary policy, an expansionary fiscal policy is thus appropriate only if long term labor and consumption taxation rates are small, and if the share of public expenditure in GDP is high. On the contrary, fiscal policy should be contractionary, in order to insure the sustainability of the long term public debt, if long term labor and consumption taxation rates are high. A contractionary fiscal policy is then also all the more appropriate as the sensitivity of government expenditure to the public debt is high, and as the labor share in the production function is high.

This study investigates the likelihood of time to bank failures in the US between 2001 and April 2023, based on data collected from the Federal Deposit Insurance Corporation's report on "Bank Failures in Brief - Summary 2001 through 2023". The dataset includes 564 instances of bank failures and several variables that may be related to the likelihood of such events, such as asset amount, deposit amount, ADR, deposit level, asset level, inflation rate, short-term interest rates, bank reserves, and GDP growth rate. We explore the efficacy of machine learning survival models in predicting bank failures and compare the performance of different models. Our findings shed light on the factors that may influence the probability of bank failures with a time perspective and provide insights for improving risk management practices in the banking industry.

Innovation has received a great attention in the creative industries literature. We propose in this study a bibliometric method to examine the literature on innovation in creative industries (ICI). A file of 656 manuscripts published on ICI between 1998 and 2022 was retrieved from the Web of Science Core Collection for analysis. The results highlight the evolution of study volume, authors, affiliated institutions and countries, author networks, keyword co-occurrences, and keyword networks. The study also includes a thematic map that highlights four types of research: driving themes (e.g., digital technology, cultural innovation, performing arts, product innovation, innovation management); core and cross-cutting themes (e.g., creativity, digitization, technology, copyright); emerging themes (e.g., gender, artificial intelligence, sustainability); and specialized and peripheral themes (e.g., gender, blockchain, digital music). We finally conclude by proposing future perspectives and a research agenda in this area.

This paper describes two novel approaches to cost estimation of manufactured products where a data set of similar products have known manufactured costs. The methods use the notion of piecewise functions and are (1) clustering and (2) splines. Cost drivers are typically a mixture of categorical and numeric data which complicates cost estimation. Both clustering and splines approaches can accommodate this. Through four case studies, we compare our approaches with the often-used regression models. Our results show that clustering especially offers promise in improving the accuracy of cost estimation. While clustering and splines are slightly more complex to develop from both a user and a computational perspective, our approaches are packaged in an open-source software. This paper is the first known to adapt and apply these two well-known mathematical approaches to manufacturing cost estimation.

A high inflation period of seven years (1978-1985) in Israel, which turned into a hyperinflation, puzzled Israeli economists, who tried to understand its causes and mechanisms. As a result, they provided fourteen different explanations. Although all of the explanations were based on the same data, the researchers’ conclusions were either different or contradictory. This situation provides a virtual laboratory for the study of the ways and methods of economic thought; it is a classical Ceteris patribus situation. This laboratory further raises other subjects and questions. Are there principal differences between the economists' explanations? Is it possible to classify these differences? How do economic explanations for inflation differ from non-economic ones? In this article, I classified thirteen economic studies and one non-economic study into five clusters. This was the methodological tool used to inquire into the economic thought in this virtual laboratory.

Motivated by the Blackorby-Schworm (1993) observation that market outcomes may differ from those originating in market-actor optimization, this paper claims that the number of banks in the market is larger than the number justified by bank profit maximization alone or in combination with bank depositor welfare maximization. This claim is made within the context of bilateral monopoly banks and intertemporal utility maximization by bank depositors. The basic policy implication towards bank population rationalization is a minimization of the deviation away from the optimal interest rate margin at every stage of the business cycle. It is meant to be an acyclical policy though the target of optimal bank population is attainable by active countercyclical policy as well. The nature of this policy issue makes the use of macroprudential measures imperative, jointly perhaps with a fiscal-monetary policy mix. A dynamic version of the model in a Cournot environment is akin to the modeling of Minsky's hypothesis of financial fragility.

Understanding the economic trends and demographic dynamics of a country is crucial for policymakers and researchers to formulate effective strategies and policies. This study aims to examine the GDP trends and aging index dynamics in Portugal from 2011 to 2021, with a focus on regional disparities and their implications for demographic challenges. The findings highlight the relationship between regional GDP and the aging index, indicating that regions with higher GDP values tend to have a relatively younger population, while regions with lower GDP values have a relatively older population. The study contributes to the existing literature on population aging by providing insights into the demographic, economic, and social implications of an aging society. It provides valuable insights into the demographic, economic, and social implications of population aging in Portugal. The findings contribute to the existing literature and can inform policymakers and stakeholders in developing targeted strategies and policies to address the specific challenges faced by each region.

Many startups look for venture capital (VC) funding to grow their business. Anecdotally, in the Southeast Asia context, startup founders who attended an elite institute of higher learning have greater access to this kind of capital, but this has not been demonstrated quantitatively. We look at a dataset of nearly 800 startups in Southeast Asia who have received VC funding in the last 5 years and look for any correlation between the founder's educational background and the amount of VC funding received. We find that founders who have obtained a postgraduate degree from an elite university receive significantly more VC funding than those who graduated from other universities. Furthermore, this effect is only seen at later stages of funding, not at the seed stage. Potential reasons for this effect could be from stronger signaling of business acumen or technical skill; or better access to funding networks.

You have a product or service for which the world has been waiting. You've scraped together enough cash to get your idea off the ground. You are confident that your business will succeed. And yet, it is often the case that a short time later you are out of business. Numbers from the U.S. Bureau of Labor Statistics indicate that about half of new businesses fail within the first five years. And with those business failures go the life savings and the dreams of the person who started the business. This article describes five finance and accounting pitfalls that should be avoided in order to increase the likelihood that a small business will succeed. Of course, the most common reason for a small business to fail is that customers don't want the product or service. But small businesses are also often killed because of predictable and preventable finance and accounting mistakes: insufficient capital, poor cash management, poor record keeping and controls, improper product pricing, and uncontrolled growth.

With the development of information technology and its application in environmental governance, the role of the internet in improving energy efficiency and reducing energy-saving potential (ESP) has attracted more attention. In this study, the slack-based model (SBM) and the unexpected model, along with the entropy method, were applied to measure China's energy-saving potential and internet development. Further, we empirically analyzed the direct effect, mediating effect, threshold effect, and regional heterogeneity of the internet on ESP. Our conclusion shows that there is a significant spatial correlation between internet penetration and ESP. Internet penetration has become an important tool for reducing ESP, but this effect shows regional heterogeneity. Human capital accumulation, financial development, and industrial upgrading are important influencing mechanisms, but indirect effects are weaker than direct effects. The impact of internet penetration on ESP is non-linear, and for improving human capital accumulation, financial development, and industrial upgrading, the role of internet popularization in energy conservation is more obvious.

We present two approaches to forecasting parameters in the SABR model. The first approach is the vector autoregressive moving-average model (VARMA) for the time series of the in-sample calibrated parameters, and the second is based on machine learning techniques called epsilon-support vector regression (ε-SVR). Using daily data of S&P 500 ETF option prices from January 1, 2014, to December 31, 2018, we first calibrate the daily values of the model parameters from the training sample, then conduct out-of-sample forecasting of parameters and pricing of options. Both approaches produce good fits between the forecasted and calibrated parameters for out-of-sample dates. A comparison study shows that using forecasted parameters as inputs, the SABR model generates better pricing results than assuming constant parameters or using lag parameters. We also discuss the market conditions under which one approach outperforms the other.

This study examines the role of the Corporate Social Responsibility Committee (CSRC) in the adoption of strategic Corporate Social Responsibility (CSR) projects that surpass regulatory requirements and basic stakeholder expectations. Our results demonstrate that the establishment of CSRCs enhances all strategic CSR mechanisms, particularly business reputation, stakeholder interaction, risk mitigation, and innovation. Additionally, strategic CSR practices exhibit a strong correlation with CSRC attributes and organizational characteristics. Specifically, the size of the CSRC is positively associated with all dimensions of strategic CSR. Furthermore, CEO membership is likely to impede risk mitigation and innovation capacity, whereas board chair membership enhances business reputation, stakeholder communication, and innovation potential. In terms of gender diversity, female CSRC members show a greater concern for business reputation and associated risks. Regarding committee functioning, increased meeting frequency has the potential to enhance various aspects of strategic CSR.

The construction and optimization of a portfolio is a complex process that has been a historically active research area in finance. For portfolios with highly correlated assets, the performance of traditional risk-based asset allocations methods such as the mean-variance (MV) model is limited when numerous assets are correlated. A novel clustering-based asset allocation method, called Hierarchical Risk Parity (HRP), provides an opportunity to mitigate these limitations in portfolio construction. HRP utilizes the hierarchical relationships between the covariance of assets in a portfolio to determine weight distributions, eliminating the need for the inversion of the covariance matrix that is required by most traditional risk-based asset allocation methods. This research examines the viability of Hierarchical Risk Parity (HRP) method in portfolio construction of a US equity portfolio and compares the performances of HRP to traditional asset allocation methods exemplified by the mean-variance (MV) method. The results of this research show that the performance of the HRP method is comparable to the performance of the MV method. Given these findings, HRP provides an advantageous approach for portfolio construction in practical scenarios where correlated assets are present in the portfolios.