Recursive robust estimation and control without commitment

In a Markov decision problem with hidden state variables, a posterior distribution serves as a state variable and Bayes’ law under an approximating model gives its law of motion. A decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are nearby when measured by their expected log likelihood ratios (entropies). Martingales represent alternative models. A decision maker constructs a sequence of robust decision rules by pretending that a sequence of minimizing players choose increments to martingales and distortions to the prior over the hidden state. A risk sensitivity operator induces robustness to perturbations of the approximating model conditioned on the hidden state. Another risk sensitivity operator induces robustness to the prior distribution over the hidden state. We use these operators to extend the approach of Hansen and Sargent [Discounted linear exponential quadratic Gaussian control, IEEE Trans. Automat. Control 40(5) (1995) 968-971] to problems that contain hidden states.     

Strategic corporate social responsibility and economic performance

This article proposes a novel Corporate Social Responsibility (CSR) index based on a Data Envelopment Analysis (DEA) model. Acknowledging the argument that companies might favour those CSR dimensions that provide strategic competitive advantages, we argue that the index can capture companies’ strategic approach to CSR. Furthermore, our findings reveal a neutral relationship between this strategic CSR index and economic performance as measured by Return on Assets (ROA) and Tobin's Q, when controlling for firm unobserved heterogeneity and past economic performance. By contrast, an equally-weighted index of the same CSR indicators is found to be negatively related with ROA, which reinforces our claim that this specific DEA-based index is a measure of strategic CSR.     

Output effects of fiscal stimulus in Central and Eastern European countries

In spite of the rapidly growing research on fiscal multipliers over recent years, little evidence has been so far accumulated in developing and emerging economies. This paper investigates the nature and the size of fiscal multipliers in Central and Eastern European (CEE) countries. Unlike most of the existing literature, we draw upon a panel vector error correction model, which appropriately captures the common long-term path of CEE countries, while allowing for different short-run dynamics, in an integrated setup. Our main results show that the spending multiplier is positive, but low on average. Moreover, its sign, significance and magnitude vary across CEE. Finally, both impulse and cumulative fiscal multipliers are sensitive to a wide range of CEE characteristics, including the exchange rate regime, the level of economic development, the fiscal stance and the openness degree.     

A comparative study of efficiency in European banking

This paper investigates whether there has been an improvement in and convergence of productive efficiency across European banking markets since the creation of the Single Internal Market. Using efficiency measures derived from DEA estimation, the determinants of European bank efficiency are evaluated using the Tobit regression model approach. The established literature on modelling the determinants of bank efficiency is then extended by recognizing the problem of the inherent dependency of DEA efficiency scores when used in regression analysis. To overcome the dependency problem, a bootstrapping technique is applied. Overall, the results suggest that since the EU's Single Market Programme there has been a small improvement in bank efficiency levels, although there is little evidence to suggest that these have converged. The results also suggest that inference on the determinants of bank efficiency drawn from non-bootstrapped regression analysis may be biased and misleading.     

Introduction to the stability of rational expectations equilibrium

This paper surveys the literature which examines the stability of the expectations that agents are assumed to have in a rational expectations equilibrium (REE). This issue is more complex than the usual statistical estimation problem because the relationship between observable variables and payoff relevant variables is endogenous. One approach taken in the literature yields convergence to a REE but requires agents to have extensive knowledge about the structure and dynamics of the model that prevails while they learn. A second approach does not assume that agents have correctly specified likelihood functions and finds that REE may not be stable.     

Pre- and Post-Global Financial Crisis Policy Multipliers

This paper estimates the change in policy multipliers in the U.S. relative to their pre-2008 financial crisis levels. It also estimates the likely impact of the 2020 stimulus packages implemented to address COVID-19. The analysis is based on an augmented Blanchard-Perotti model that allows for the dynamic effects of shocks to the central bank balance sheet, real interest rates and debt levels on economic activity. The results suggest that expenditure multipliers have fallen post-2008, mostly because of higher government debt, implying that the effectiveness of fiscal policy has declined. They also suggest that the impact of quantitative easing is beneficial, but requires sizable interventions to have noticeable effects on real GDP. Because of rising debt stocks, dealing with a crisis is becoming more and more costly despite the current low interest rate environment.     

Dynamic coordinating non-equilibrium

Neo-Walrasian conceptualizations and DSGE models are incompatible with the emergence of coordination and discoordination in economic activity. While many conceptualizations stemming from the Austrian tradition are generally consistent with these fundamental problems, their process driven approach is hampered by the use of equilibrium constructs. This paper argues for the adoption of formal models that avoid this problem by addressing the following questions. Why should Austrian macroeconomists model? Where do models fit in with respect to pure and applied theory? How to model without equilibrium? To answer this final question I present a structure that aids in the construction and communication of such models.     

WHAT CAN WE LEARN ABOUT CONGRESSIONAL POLITICS FROM DIMENSIONAL STUDIES OF ROLL-CALL VOTING?

How many dimensions are there in Congressional roll-call votes? What do dimensions tell us about Congressional politics? Poole and Rosenthal have found one or a very few dimensions. Earlier work has identified problems with Poole and Rosenthal's dimensional fitting method. This paper finds additional problems, showing that when legislators’relative intensity of preferences varies across issues, the Poole and Rosenthal approach will fail. Specifically, while redistributive issues fit their model, distributive and regulative issues allow gains from trade, and thus vote-trading and coalition-building. Roll-call data show voting patterns inconsistent with the Poole and Rosenthal model.     

A program for algebraic and qualitative comparative statics and stability analysis

This paper presents a computer program designed by the author which determines algebraically and qualitatively both short- and long-run comparative statics multipliers for standard linear or linearized economic models. When the model is dynamic, i.e., when it involves linear of linearized differential equations, the program also provides the algebraic expressions and the qualitative signs for the coefficients of the characteristic polynomial.     

Returns to scale in DEA models for performance evaluations

The technology industry is a major driving force in Taiwan's economic development. The Taiwan government employed technology development programs (TDPs) to stimulate industrial technology research and development to enhance industry competitiveness. This paper uses Data Envelopment Analysis (DEA), a nonparametric approach, to evaluate the relative efficiency of decision-making units (DMUs) that use multiple inputs to produce multiple outputs, to evaluate the relative managerial efficiency of TDPs. The inputs are human resources and expenditures. The outputs are patents and technology outcomes. We investigated TDP performance over the period from 1999 to 2003. This study uses CCR and BCC models, which are DEA model variants, to calculate efficiency indexes. CCR is adopted under the assumption of constant returns to scale. BCC is used to understand the variable returns to scale, including the constant, decreasing and increasing. We found that TDPs in the material and chemical engineering fields in 1999 and 2001, machinery and aerospace fields in 1999, and communication and optoelectronics fields in 2002 had better performance than the other TDPs. We provide potential improvements for inefficient DMUs.     

The Ricardian equivalence hypothesis: evidence from Bangladesh

In this paper, a probabilistic discrete choice approach is used to examine the influence of economic and non-economic factors on the choice of medical specialty by new physicians. A two level nested logit model is estimated that relaxes the independence from irrelevant alternatives assumption, and allows for a potentially more realistic pattern of substitution across specialty choices. The results from this specification are compared to those obtained from joint and conditional logit models. The findings, which are relatively robust across models, indicate that economic incentives play an important role in the specialty choice process, in particular, expected hours worked and medical school indebtedness. Physician tastes for specialties also appear to have an important influence.     

Procedural Rationality and Institutions: The Production of Norms by Means of Norms

This paper deals with a cognitivist approach to the problem of how social and economic institutions are formed. The economic framework I use is Simon's model of procedural rationality, integrating a cognitivist approach into a game structure. In game theory norms are seen as conventions, but not all institutions can be explained by game theory models. In cognition-based approaches, the creation and maintenance of institutions is the outcome of a search for satisficing norms. According to Simon and Newell (1972), agents faced with problems to solve visualise a problem as an area of potential situations to examine in order to establish analogical problem structures. In my approach, a norm can be defined within a system of norms that form in a historical-evolutionary dimension, suggesting a path in norm-forming processes.     

Unveiling covariate inclusion structures in economic growth regressions using latent class analysis

We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian model averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model space formed by linear regression models reveals interesting patterns of complementarity and substitutability across economic growth determinants.     

Linearity of the return to education and self selection

This paper investigates the earnings-education profile in Spain. First no functional form is imposed on this relation but instead dummy variables are used for each year of education. Second, different alternatives are analysed until the best parametric form is found. Moreover problems related to the self selection of individuals and to the segmentation of the labour market based on the educational level are considered. The main results indicate that the effect of education on earnings is not significant until individuals finish secondary education and from there onwards the relationship can be considered linear.     

The Welfare Economic Theory of Green National Accounts

This paper takes a critical look at the literature on green national accounts. The problem studied is to find a linear index of economic variables that responds to perturbations in the same direction as social well-being. The thesis of a large literature, that net national product (which is a flow) is that index in closed economies, is shown in some interpretations to be simply false and in others to suffer from deep estimation problems. It is argued that capital depreciation using shadow prices should certainly be included in national accounts, but that the right welfare index is a comprehensive measure of wealth, defined as the shadow value of an economy’s stock of all capital assets. It is shown that comprehensive wealth is usable as a criterion for policy evaluation as well as for determining sustainable economic development.     

Robust estimation and control under commitment

In a Markov decision problem with hidden state variables, a decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are nearby as measured by their expected log likelihood ratios (entropies). Sets of martingales represent alternative models. Within a two-player zero-sum game under commitment, a minimizing player chooses a martingale at time 0. Probability distributions that solve distorted filtering problems serve as state variables, much like the posterior in problems without concerns about misspecification. We state conditions under which an equilibrium of the zero-sum game with commitment has a recursive representation that can be cast in terms of two risk-sensitivity operators. We apply our results to a linear quadratic example that makes contact with findings of T. Ba?ar and P. Bernhard [H^∞-Optimal Control and Related Minimax Design Problems, second ed., Birkhauser, Basel, 1995] and P. Whittle [Risk-sensitive Optimal Control, Wiley, New York, 1990].     

Reducing Greenhouse Gas Emissions in Fisheries: The Case of Multiple Regulatory Instruments in Sweden

The fishing sector is a candidate for efficient climate policies because it is commonly exempted from greenhouse gas taxes and the fundamental problem of using a common pool resource is far from optimally solved. At the same time, fisheries management has other objectives. This study uses Swedish fisheries to analyse how the fishing sector and its climate impact are affected by regulations aiming at: (1) solving the common pool problem (2) taxing greenhouse gas emissions and (3) maintaining small-scale fisheries. The empirical approach is a linear programming model where the effects of simultaneously using multiple regulations are analyzed. Solving the common pool problem will lead to a 30 % reduction in emissions and substantially increase economic returns. Taxing greenhouse gas emissions will further reduce emissions. Policies for maintaining the small-scale fleet will increase the size of this fleet segment, but at the cost of lower economic returns. However, combining this policy with fuel taxes will reduce the size of the small-scale fleet, thus counteracting the effects of the policy. If taxation induces fuel-saving innovations, it is shown that this will affect not only emissions and fleet structure, but also quota uptake.     

Explaining time variation in geographic price dispersion

The pattern of price dispersion significantly varies over time and across locations. Using a detailed dataset with product-level retail prices, we examine the role of time-varying factors in shaping the time variation of price dispersion. We find that price dispersion variation in an integrated region is mainly driven by oil prices, while the variation in a segmented region is attributed to dispersion in real income. We also find that dispersion in value-added tax rates explains a significant portion of price dispersion fluctuations in both geographic dimensions. This paper offers new evindence on the trade-off that exists for the role of time-varying factors as contributors to price dispersion variation by highlighting their relative importance across different dimensions of economic geography.     

Wage bargaining and employment revisited: separability and efficiency in collective bargaining*

We analyse the two-dimensional Nash bargaining solution (NBS) by deploying the standard labour market negotiations model of McDonald and Solow. We show that the two-dimensional bargaining problem can be decomposed into two one-dimensional problems, such that the two solutions together replicate the solution of the two-dimensional problem if the NBS is applied. The axiom of “independence of irrelevant alternatives” is shown to be crucial for this type of decomposability. This result has significant implications for actual negotiations because it allows for the decomposition of a multi-dimensional bargaining problem into one-dimensional problems – and thus helps to facilitate real-world negotiations.     

An operational,nonlinear input–output system

We develop a scale-dependent nonlinear input–output model which is a practical alternative to the conventional linear counterpart. The model contemplates the possibility of different assumptions on returns to scale and is calibrated in a simple manner that closely resembles the usual technical coefficient calibration procedure. Multiplier calculations under this nonlinear version offer appropriate interval estimates that provide information on the effectiveness and variability of demand-driven induced changes in equilibrium magnitudes. In addition, and unlike linear multipliers, the nonlinear model allows us to distinguish between physical and cost effects, the reason being that the traditional dichotomy between the price and quantity equations of linear models no longer holds. We perform an empirical implementation of the nonlinear model using recent interindustry data for Brazil, China and United States. When evaluating the robustness of the derived marginal output multipliers and the induced cost effects under the nonlinear approach, the results indicate that marginal indicators in physical terms can be perfectly used to infer average impacts; this is not the case, however, for the derived cost effects where average measures are seen to be more adequate. At the computational level, the analysis proves the operational applicability of the nonlinear system while at the methodological level shows that scale effects are relevant in determining sectoral multipliers.