Documents Antal, Miklós 4 results

"Climate policy has been mainly studied with economic models that assume representative, rational agents. However, it aims at changing behavior associated with carbon-intensive goods that are often subject to bounded rationality and social preferences, such as status and imitation. Here we use a macroeconomic multi-agent model with such features to test the effect of various policies on both environmental and economic performance. The model is particularly suitable to address distributional impacts of climate policies, not only because populations of many agents are included, but also as these are composed of different classes of households driven by specific motivations. We simulate various policy scenarios, combining in different ways a carbon tax, a reduction of labor taxes, subsidies for green innovation, a price subsidy to consumers for less carbon-intensive products, and green government procurement. The results show pronounced differences with those obtained by rational-agent model studies. It turns out that demand-oriented subsidies lead to lower unemployment and higher output, but perform less well in terms of carbon emissions. The supply-oriented subsidy for green innovation results in a significant reduction of carbon emissions with a slight reduction of unemployment."

"In this paper we present a sector-based approach to investigate whether green growth – combining economic growth with environmental sustainability – is feasible. Our approach considers the relation between on the one hand carbon dioxide emissions per dollar of output (what we will call carbon intensity) and on the other growth in economic output and labor productivity, at the level of production sectors. Carbon intensity (CI) is calculated in two ways: as direct CO2 emissions from each sector, which can be seen to immediately result from the processes in the respective sector; and as total, direct plus indirect, emissions, by using environmentally-extended input-output tables. The analysis covers Denmark, Germany and Spain for the period 1995-2007. We calculate correlations over time between sectoral CIs and a range of economic indicators: sectoral total and relative output, final demand, value added, and so-called output and valued-added productivity indicators, and their change. The findings are similar for the two types of CI indicators. The bad news for green growth is that relatively clean sectors do not seem to be more productive than dirtier ones, and neither show higher productivity growth. Sectors associated with high carbon intensity grew more in absolute terms than those with low carbon intensity. The share of these sectors increased suggesting that green growth requires a very rapid pace of decarbonization, or the economy as a whole to shrink. Longer-term sectoral growth on the other hand, as expressed by a change in value added, does not seem to be positively correlated with carbon intensity."

"We raise fundamental questions about macroeconomics relevant to escaping the financial and economic crisis and shifting to a sustainable economy. First, the feasibility of decoupling environmental pressure from aggregate income is considered. Decoupling as a single environmental strategy is found to be very risky. Next, three main arguments for economic growth are examined: growth as progress, growth to avoid economic instability, and growth to offset unemployment due to labour productivity improvements. For each, we offer orthodox, heterodox and new responses. Attention is paid to progress indicators, feedback mechanisms affecting business cycles, and strategies to limit unemployment without the need for growth. Besides offering an economy-wide angle, we discuss the role of housing and mortgage markets in economic cyclicality. Finally, interactions between real economic and financial-monetary spheres are studied. This includes money creation, capital allocation and trade-offs between efficiency and operating costs of financial systems. Throughout, environmental and transition implications are outlined."

"Working time reduction may be one of the great achievements of the 21st century, potentially delivering environmental, social, and economic benefits. However, implementation at the level of organizations is not straightforward. Reliable data on working hours are needed to track changes, so the limited availability or poor quality of data may prevent certain types of reductions. Here we explore the factors that influence data quality in different contexts on the basis of 28 expert interviews. We list more than ten interrelated factors that matter, including descriptors of the work context, the motivations and functions of measurements, definitions of working time applied, as well as approaches and tools of measurements. For each of these factors, we highlight cases when data quality can be expected to be high and low. At the micro level, this facilitates the implementation and assessment of reduction programmes. At the macro level, it is a first step towards more realistic models, which helps to establish policy priorities concerning the role of direct regulation as opposed to cultural and institutional changes driving reductions in working hours."