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This study aims to elucidate the dynamics of monetary and fiscal policy interactions in Brazil, focusing on the impacts of positive shocks in government consumption and interest rates. By comparing rational and behavioral agent responses, it clarifies how these frameworks influence gross domestic product (GDP), inflation, private and government consumption and nominal interest rates.

The study employs a new Keynesian dynamic stochastic general equilibrium (DSGE) model with Bayesian estimation from 2000Q1 to 2022Q4, capturing rational and behavioral behaviors with adjustments for Brazilian economic idiosyncrasies. Impulse response functions (IRF) assess the dynamic effects of policy shocks, providing a comparative analysis of the two frameworks.

Behavioral agents show greater initial sensitivity to policy shocks, causing more pronounced fluctuations in GDP, inflation and private consumption compared to rational agents. Over time, the behavioral approach leads to a more robust recovery, while the rational approach results in a quicker return to equilibrium but less pronounced long-term recovery. The study also finds fiscal policy can partially offset the negative impacts of monetary tightening, with a more delayed effect in the behavioral model.

This paper provides insights into the interplay between monetary and fiscal policies under different agent expectations, emphasizing the importance of incorporating behavioral elements into macroeconomic models to better capture policy dynamics in emerging markets.

This paper surveys the treatment of expectations in estimated Dynamic Stochastic General Equilibrium (DSGE) macroeconomic models.

A recent notable development in the empirical macroeconomics literature has been the rapid growth of papers that build structural models, which include a number of frictions and shocks, and which are confronted with the data using sophisticated full-information econometric approaches, often using Bayesian methods.

A widespread assumption in these estimated models, as in most of the macroeconomic literature in general, is that economic agents' expectations are formed according to the Rational Expectations Hypothesis (REH). Various alternative ways to model the formation of expectations have, however, emerged: some are simple refinements that maintain the REH, but change the information structure along different dimensions, while others imply more significant departures from rational expectations.

I review here the modeling of the expectation formation process and discuss related econometric issues in current structural macroeconomic models. The discussion includes benchmark models assuming rational expectations, extensions based on allowing for sunspots, news, sticky information, as well as models that abandon the REH to use learning, heuristics, or subjective expectations.

Researchers have proposed characteristics‐based pricing models as an alternative to risk‐based pricing models. While supported empirically, these characteristic‐based models lack theoretical support. This paper seeks to reformulate an asset‐pricing model (RAPM) to demonstrate why firm characteristics help to explain stock returns.

The RAPM is grounded in an economic setting where two groups of agents hold different beliefs about firm fundamental values, and the more sophisticated group (rationals) adopts contrarian strategies against the naïve group (quasis). The model is derived in a static equilibrium within the consumption‐investment framework with heterogeneous agents.

The key theoretical result is a parsimonious equation of cross‐sectional expected returns that not only are specified by the traditional risk‐return relation, but also are determined by contrarian adjustments at both market‐wide and firm‐specific levels. When the model is taken to empirical specifications, it leads to consistent explanations for the behaviors of growth and value stocks, and for size and book‐to‐market effects.

The RAPM is a one‐period model that assumes that “rationals” have perfect knowledge about “quasis” sentiment parameter and their relative market weights. In future research, it is planned to extend this static model to multiple periods to incorporate a learning process by which “rationals” learn these parameters over time.

The RAPM clearly identifies four criteria for implementing arbitrage opportunities in investments. These criteria formalize the common practices in the mutual/hedge fund industry.

The paper develops an original framework that formally supports the characteristics‐based models. It offers insights for researchers in behavioral finance and guidelines for investment practitioners.

The different types of estimators of rational expectations models are surveyed. A key feature is that the model′s solution has to be taken into account when it is estimated. The two ways of doing this, the substitution and errors‐in‐variables methods, give rise to different estimators. In the former case, a generalised least‐squares or maximum‐likelihood type estimator generally gives consistent and efficient estimates. In the latter case, a generalised instrumental variable (GIV) type estimator is needed. Because the substitution method involves more complicated restrictions and because it resolves the solution indeterminacy in a more arbitary fashion, when there are forward‐looking expectations, the errors‐in‐variables solution with the GIV estimator is the recommended combination.

The purpose of this study is to fill the gap by investigating the relationship between age and other demographics on decision-making and leadership styles of executives in the non-profit sector.

This study is a quantitative research using correlation analysis and analysis of variance. The quantitative approach establishes facts, makes predictions and tests stated hypothesis and used the Pearson correlation coefficient, the ANOVA and the two-way analysis of variance. This study used surveys to collect data.

H1 states that there will be no significant difference in the decision-making models used among non-profit organizational leaders (rational, intuitive, dependent, spontaneous and avoidant) based on demographic variables: gender and age. H2 states that there will be no significant difference in the leadership style used among non-profit organizational executives (selling, telling, delegating and participating) and different dimensions of demographic variables: gender and age.

This study explored the relationship between the demographics, age and gender and the decision-making models (rational, intuitive, dependent, spontaneous and avoidant) and leadership styles (selling, telling, delegating and participating) of executives in non-profit organizations. The age of the executives also showed to be important factors that influenced executive’s leadership styles and decision-making models as well.

Rational decision-making as reflected to in this study has been used by older, possibly more experienced non-profit executives. This model is favorable towards making decisions on complicated issues. The final choice rational decision-makers select will maximize the outcome; it is assumed that the decision-maker will choose the alternative that rates the highest and get the maximum benefits (Robbins and Decenzo, 2003, pp. 141-142). The researcher suggests that non-profit executives, especially the younger executives, should attend management and leadership conferences that focus on rational decision-making models as concerns business strategies and making the best choices based on possible alternatives.

Rational decision-making as reflected to in this study has been used by older, possibly more experienced non-profit executives. This model is favorable towards making decisions on complicated issues. The final choice rational decision-makers select will maximize the outcome; it is assumed that the decision-maker will choose the alternative that rates the highest and get the maximum benefits (Robbins and Decenzo, 2003, pp. 141-142). The researcher suggests that non-profit executives, especially the younger executives, should attend management and leadership conferences that focus on rational decision-making models as concerns business strategies and making the best choices based on possible alternatives.

This is an original piece of research that contributes to the literature on leadership style.

This article assesses a rational-choice model of bureaucratic behaviour - the bureau-shaping model - as an explanation of budget-making in British local government. The bureau-shaping model is essentially a reconstructed rational-choice model of bureaucratic behaviour in liberal democratic states, which emerged from critiques of its rival budgetmaximising model. The explanatory power of the bureau-shaping model is significantly superior to the budget-maximising model. However, the explanatory power of the bureaushaping model is limited because, as a supply-side model, it cannot explain how budgets are demanded and controlled by political sponsors, who in turn are constrained politically. Budgetary decision-making takes place in a political arena where both supply and demand are mediated; a supply-side model, at best, can explain only half the budget-story.

The purpose of this paper is to show how the taxation effect on cross-state smuggling can be a valid instrumental variable for lagged and future consumption together with the local price series.

On the same grounds, the authors raise the question using the rational-addiction model by noticing that the neighboring price differentials really capture the possible smuggling or bootlegging effects.

Moreover, the authors look into the extended model to test the key condition that the expected future financial consequences will affect the current consumptions.

This supports the rational-addiction model, which can be used to plan the taxation for the forward-looking consumptions.

The authors study the explanatory power of investor rationality and irrationality for value and momentum portfolios. We also examine the relationships during financial crisis events, namely, the US subprime mortgage crisis (2007–2009) and the European debt crisis (2011–2013).

This study examines the influence of investors’ rationality and irrationality on the US stock market, using the multiple linear regression model and the stepwise regression model. Technically, the stepwise regression uses the machine-learning technique, with specific testing methods — forward selection, backward selection and stepwise selection — to find the best-fit model, according to Akaike’s Information Criterion (AIC). Thus, in this study, we will show the best model, as tested by the stepwise regression model.

Our empirical results contribute to the importance of reasons and emotions for stock-market returns and conclude that rationality and irrationality simultaneously explain the value and momentum portfolios, as well as the ETF portfolios. Also, the rational and irrational explanatory powers differ, depending on portfolios and different periods. Rational factors usually explain the volatility of the return to a greater extent than irrational factors. Moreover, during a financial crisis, the irrational factors remarkably increase their importance in explaining returns, especially for the ETF portfolios.

We expect this study’s contribution will show not only academic contribution but also benefit many stakeholders in the financial market. Investors and traders can identify various irrational factors of trading — for example, taking a long position during the panic in the market following the indicators in the models. Managers also reconsider the cost of the company by adding irrational factors when computing the equity’s expected return. Similarly, stock exchanges can adequately adjust their circuit breaker during a pessimistic-investor period. Finally, regulators can evaluate a complete picture of the stock market by adding irrational factors into their considerations.

The Neoclassical approach to analysing personal choice is compared with an approach contained in a Biblical Christian mode of analysis. This paper compares the Neoclassical and Christian positions via analysis of characteristics of the Neoclassical rational choice model. The main characteristic examined is a basic assumption of the rational choice model that human choice is explained as the optimisation of utility via rational self‐interest. The two positions are compared in terms of how they treat self‐interest and rationality, the degree to which basic assumptions about human behaviour are specified, the importance they attach to the realism of assumptions underlying their models, and the explanatory and predictive purposes for which the models are used. The conclusion of the comparison is that the Biblical Christian perspective encompasses the variables regarded as important in Neoclassical explanation, but presents them in the context of a more embracing worldview perspective than the Neoclassical. This Christian belief perspective is applicable to human behaviour in both “economic” and “non‐economic” domains.