Mitigation from a cross-sectoral perspective

We investigate whether income inequality affects subsequent growth in a cross-country sample for 1965-90, using the models of Barro (1997), Bleaney and Nishiyama (2002) and Sachs and Warner (1997), with negative results. We then investigate the evolution of income inequality over the same period and its correlation with growth. The dominating feature is inequality convergence across countries. This convergence has been significantly faster amongst developed countries. Growth does not appear to influence the evolution of inequality over time. Outline

https://www.econstor.eu/bitstream/10419/81822/1/02-28.pdf

Economic growth and income inequality

Recent statistical techniques, including nonlinear programming, have been added to a basic survey of equilibrium systems, comparative statistics, consumer behavior theory, and cost and production theory.

Foundations of Economic Analysis

We develop a cointegrating nonlinear autoregressive distributed lag (NARDL) model in which short- and long-run nonlinearities are introduced via positive and negative partial sum decompositions of the explanatory variables. We demonstrate that the model is estimable by OLS and that reliable long-run inference can be achieved by bounds-testing regardless of the integration orders of the variables. Furthermore, we derive asymmetric dynamic multipliers that graphically depict the traverse between the short- and the long-run. The salient features of the model are illustrated using the example of the nonlinear unemployment-output relationship in the US, Canada and Japan.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2344046_code1643826.pdf?abstractid=1807745&mirid=5

Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework

This paper introduces endogenous and directed technical change in a growth model with environmental constraints. The final good is produced from “ dirty” and “ clean” inputs. We show that: (i) when inputs are sufficiently substitutable, sustainable growth can be achieved with temporary taxes/subsidies that redirect innovation toward clean inputs; (ii) optimal policy involves both “ carbon taxes” and research subsidies, avoiding excessive use of carbon taxes; (iii) delay in intervention is costly, as it later necessitates a longer transition phase with slow growth; and (iv) use of an exhaustible resource in dirty input production helps the switch to clean innovation under laissez-faire. (JEL O33, O44, Q30, Q54, Q56, Q58)

/pdf/the-environment-and-directed-technical-change-2mflbkatdz.pdf

The Environment and Directed Technical Change

Economists have long advocated the widespread use of carbon pricing as the chief policy to combat climate change. Consensus is growing also among governments and businesses on the fundamental role of carbon pricing in the decarbonization of the economy. For governments, carbon pricing can be a source of revenue, which is particularly important in an economic environment of budgetary constraints. Businesses increasingly evaluate the impact of mandatory carbon prices on their operations and use them as a tool to identify potential climate risks and revenue opportunities. Finally, long-term investors use carbon pricing to analyze the potential impact of climate change policies on their investment portfolios, allowing them to reassess investment strategies and reallocate capital toward low-carbon or climate-resilient activities. By and large, carbon pricing takes two basic forms: a carbon tax and an emission trading system. In this chapter, we briefly review these two instruments from a conceptual standpoint. We then review the actual experience with these instruments with reference to European countries and the European Union (EU), the region where those policies have been introduced and implemented first. 

Carbon Pricing from the Origin to the European Green Deal

Each semester the THINK project publishes two research reports based on topics proposed by the European Commission

The Impact of Climate and Energy Policies on the Public Budget of EU Member States

This paper reviews recent developments in the study of the so-called "double dividend", i.e. the possibility of improving the environment and, at the same time, reducing the distortions of the tax system through revenue-neutral green taxes. Recent modeling advances are considered at both the theoretical and the empirical levels. In particular, we note that the most significant theoretical advances have been made in the direction of allowing for imperfectly competitive markets, especially the market for labor. At the same time, we argue that empirical work, particularly on the "employment double dividend", is still relatively scant and that much more needs to be done both in the direction of more realistic empirical models and of an extended sensitivity analysis of the main findings.

The Double Dividend Issue: Modelling Strategies and Empirical Findings

The purpose of this paper is to develop a model that integrates inventory and labor decisions. We extend a model of inventory behavior to include a detailed specification of the role of labor input in the production process and of the costs associated with it. In particular, we distinguish between employment, hours and effort per worker, and allow for adjustment costs associated with employment changes. We assume that the requirement function for effective hours has a general trans-logarithmic form, and derive an estimable system of Euler equations for inventories and employment with implied cross-equation restrictions. The econometric results shed light on several important topics, including the shape of the marginal cost of output and the role of labor hoarding as an explanation of procyclical productivity and the persistence of inventory stocks. Moreover, they raise questions about the adequacy of commonly used specifications such as Cobb-Douglas approximations to the production process and the definition of labor input as the product of employment and effective hours worked per worker.

Inventories, Employment and Hours

The complexity of integrated assessment models (IAMs) prevents the direct appreciation of the impact of uncertainty on the model predictions. However, for a full understanding and corroboration of model results, analysts might be willing, and ought to identify the model inputs that influence the model results the most (key drivers), the direction of change associated with the variation of a given input and the overall model structure (interaction analysis). We show that such information is already contained in the data set produced by Monte Carlo simulations commonly used in IAM studies and that can be extracted from it without additional calculations. Our discussion is guided by an application of the proposed methodologies to the well-known DICE model of William Nordhaus (2008). A comparison of the proposed methodology to approaches previously applied on the same model shows that robust insights concerning the dependence of future atmospheric temperature, global emissions and current carbon costs and taxes on the model's exogenous inputs can be obtained. The method avoids the fallacy of a priori deeming the important factors based on the sole intuition

Uncertainty in Integrated Assessment Modelling: Can Global Sensitivity Analysis Be of Help?

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Marzio Galeotti

Author Tools

Chat about Author