Nonlinear dynamics in economic modelling

Decisions in Economics and Finance -     

The influence of managers' awareness of climate change,perceived climate risk exposure and risk tolerance on the adoption of corporate responses to climate change

Uncertainties posed by climate change limit companies' ability to understand implications of global warming on business and society at large, hampering the adoption of tangible organizational responses to climate change. Understanding climate action thus requires to investigate influential factors of decision-making under uncertainty, which implies acknowledging managerial interpretations and perceptions about climate issues. Drawing insights from the literature on climate inaction and from corporate sustainability literature, the present study examines awareness of climate change and perceived exposure to climate risks as antecedents of corporate responses to climate change, drawing on a survey of managers of Italian manufacturing companies. In addition, the study tests the moderation of risk tolerance on the relation between perceived climate risk exposure and climate action, suggesting that risk attitudes are a significant factor of decision-making under climate uncertainty. The results support the hypothesis of the model and thus provide several contributions to the literature on business and climate change. Managerial implications and avenues for future research are also discussed.     

Enhancing environmental information transparency through corporate social responsibility reporting regulation

This research aims to contribute to the scientific debate about the lack of interlinkages between mandatory non-financial reporting and sustainable business models. For our purposes, a counter-accounting analysis was conducted on the non-financial reports of a sample of 145 Italian firms interested by the Directive 2014/95/EU effects. Specifically, the study adopts an empirical approach to evaluate environmental information transparency, which represents one of the main critical issues concerning the non-financial declarations prepared by European Italian Public Interest Entities (PIEs) to comply with Directive 2014/95/EU. The results highlight that corporate governance and report characteristics affect environmental transparency. Furthermore, the results confirm the overall attitude to avoid the disclosure of unfavourable or unavailable environmental information through impression management strategies. Finally, the analysis underlines the opportunities for policymakers to rethink mandatory non-financial reporting to sustain the ecological transition of European PIEs.     

Effects of redistributing policy support on farmers’ technical efficiency

The objective of this article is twofold: first, investigating the relationship between technical efficiency and decoupled direct payments of a sample of Italian farms prior to the application of the 2014–2020 Common Agricultural Policy reform; second, evaluating possible implications of alternative scenarios about distribution of direct payments on technical efficiency. To these aims, a stochastic frontier analysis is adopted. Results indicate that direct payments produce significant effects on technical efficiency in specialized farms, which received higher levels of support. However, effects are contrasting. Moreover, results show that redistribution of policy subsidies may negatively impact on technical efficiency to an extent depending upon the criterion of redistribution applied. Finally, some policy suggestions are given.     

Optimal regulation under imperfect enforcement: Permits,tickets, or both?

Economic activity is often regulated through both permits and tickets (subsequent inspections). We study the effectiveness of such policies where corruption and an underground economy make enforcement imperfect. In the theoretical model, asymmetric information justifies regulatory action which is enforced by corruptible bureaucrats. We find that regulation through permits alone is useless when corruption exists, while tickets still offer some benefit. Surprisingly, we also find that a system with both permits and tickets achieves welfare that is higher than that which can be achieved with only tickets—that combining the two mechanisms has an effect that is greater than the “sum of the parts.”     

Learning, monetary policy rules, and macroeconomic stability

Several papers have documented a regime switch in US monetary policy from ‘passive’ and destabilizing in the pre-1979 period to ‘active’ and stabilizing afterwards. These studies typically work with DSGE models with rational expectations.This paper relaxes the assumption of rational expectations and allows for learning instead. Economic agents form expectations from simple models and update the parameters through constant-gain learning. In this setting, the paper aims to test whether monetary policy may have been a source of macroeconomic instability in the 1970s by inducing unstable learning dynamics.The model is estimated by Bayesian methods. The constant-gain coefficient is jointly estimated with the structural and policy parameters in the system.The results show that monetary policy was respecting the Taylor principle also in the pre-1979 period and, therefore, did not trigger macroeconomic instability.     

Production smoothing, firms' heterogeneity, and financial constraints: evidence from a panel of UK firms

In this paper we provide an empirical analysis of heterogeneityin firms' inventory behavior, using a panel of UK manufacturingfirms. We first investigate how the relative variance of productionand sales differs across firms. We then use variants of thelinear quadratic inventory model in order to analyze potentialheterogeneity in firms' incentives to smooth production. Theresults suggest that incentives to smooth production are notprevalent This conclusion also holds when firms are partitionedaccording to whether they are more or leu likely to face finanrialconstraints.     

A New Approach to the Study of Jobless Recoveries

This article is concerned with the measurement of jobless recoveries and the elements that may explain their emergence. We first introduce a measure that maps the various elements that define a jobless recovery into a single number that we label the jobless recovery depth. We then construct a database of 389 state‐level observations and study the cross‐sectional variations that emerge. We find that jobless recoveries in the United States are not a nation‐wide phenomena, but a local event confined within a cluster of states that expands slowly between 1975 and 2015. We find the state‐level evidence to be consistent with theories that link jobless recoveries to unusually long expansionary periods, less dynamic labor markets, and the advent of the great moderation. The evidence is not consistent with theories that link them to decreases in union power, increases in income inequality, or increases in health care costs.     

Assessing financial distress dependencies in OTC markets: a new approach using trade repositories data

In this paper, we study the relationships among financial market sub-segments as a way to identify potential financial distress through increased co-movements among them. To study how sub-markets are mutually co-dependent, we combine granular data on over-the-counter derivatives by trade repositories and the joint probability of distress (JPoD) approach introduced by the International Monetary Fund. We define an indicator that combines several distress drivers and observe that results on co-dependencies are similar to those that would be expected: similarities between financial and contractual terms seem to be responsible for stronger co-movements among sub-markets. However, high values for JPoD even in correspondence of quite dissimilar sub-markets suggest the presence of other drivers that should be investigated in future research. To the best of our knowledge, this is the first empirical study on systemic risk assessment based on micro-founded trade repositories’ data on interest rate swaps.     

Consumption optimization for recursive utility in a jump-diffusion model

In this paper, we consider a market model with prices and consumption following a jump-diffusion dynamics. In this setting, we first characterize the optimal consumption plan for an investor with recursive stochastic differential utility on the basis of his/her own beliefs, then we solve the inverse problem to find what beliefs make a given consumption plan optimal. The problem is viewed in general for a class of homogeneous recursive utility, and later we choose a logarithmic model for the utility aggregator as an explicitly computable example. When beliefs, represented via Girsanov’s theorem, get incorporated into the model, the change of measure gives rise, up to a transformation, to a backward stochastic differential equation whose generator exhibits a quadratic behavior in the Brownian component and a locally Lipschitz one in the jump component, which is solvable on the basis of some recent results.