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Richard S. J. Tol

Publications and source records attributed to Richard S. J. Tol.

At least 37 records · Page 2Linked to original sources
arXiv2023

Actualised and future changes in regional economic growth through sea level rise

This study investigates the long-term economic impact of sea-level rise (SLR) on coastal regions in Europe, focusing on Gross Domestic Product (GDP). Using a novel dataset covering regional SLR and economic growth from 1900 to 2020, we quantify the relationships between SLR and regional GDP per capita across 79 coastal EU & UK regions. Our results reveal that the current SLR has already negatively influenced GDP of coastal regions, leading to a cumulative 4.7% loss at 39 cm of SLR. Over the 120 year period studied, the actualised impact of SLR on the annual growth rate is between -0.02% and 0.04%. Extrapolating these findings to future climate and socio-economic scenarios, we show that in the absence of additional adaptation measures, GDP losses by 2100 could range between -6.3% and -20.8% under the most extreme SLR scenario (SSP5-RCP8.5 High-end Ice, or -4.0% to -14.1% in SSP5-RCP8.5 High Ice). This statistical analysis utilising a century-long dataset, provides an empirical foundation for designing region-specific climate adaptation strategies to mitigate economic damages caused by SLR. Our evidence supports the argument for strategically relocating assets and establishing coastal setback zones when it is economically preferable and socially agreeable, given that protection investments have an economic impact.

econ.GN↗
arXiv2023

Endogenous preference for non-market goods in carbon abatement decision

Carbon abatement decisions are usually based on the implausible assumption of constant social preference. This paper focuses on a specific case of market and non-market goods, and investigates the optimal climate policy when social preference for them is also changed by climate policy in the DICE model. The relative price of non-market goods grows over time due to increases in both relative scarcity and appreciation of it. Therefore, climbing relative price brings upward the social cost of carbon denominated in terms of market goods. Because abatement decision affects the valuation of non-market goods in the utility function, unlike previous climate-economy models, we solve the model iteratively by taking the obtained abatement rates from the last run as inputs in the current run. The results in baseline calibration advocate a more stringent climate policy, where endogenous social preference to climate policy raises the social cost of carbon further by roughly 12%-18% this century. Moreover, neglecting changing social preference leads to an underestimate of non-market goods damages by 15%. Our results support that climate policy is self-reinforced if it favors more expensive consumption type.

econ.GN↗
arXiv2023

Baumol's Climate Disease

We investigate optimal carbon abatement in a dynamic general equilibrium climate-economy model with endogenous structural change. By differentiating the production of investment from consumption, we show that social cost of carbon can be conceived as a reduction in physical capital. In addition, we distinguish two final sectors in terms of productivity growth and climate vulnerability. We theoretically show that heterogeneous climate vulnerability results in a climate-induced version of Baumol's cost disease. Further, if climate-vulnerable sectors have high (low) productivity growth, climate impact can either ameliorate (aggravate) the Baumol's cost disease, call for less (more) stringent climate policy. We conclude that carbon abatement should not only factor in unpriced climate capital, but also be tailored to Baumol's cost and climate diseases.

econ.TH↗
arXiv2023

The Social Cost of Carbon

The social cost of carbon is the damage avoided by slightly reducing carbon dioxide emissions. It is a measure of the desired intensity of climate policy. The social cost of carbon is highly uncertain because of the long and complex cause-effect chain, and because it quantifies and aggregates impacts over a long period of time, affecting all people in a wide range of possible futures. Recent estimates are around $\$$80/tCO$_2$.

econ.GN↗
arXiv2023

The fiscal implications of stringent climate policy

Stringent climate policy compatible with the targets of the 2015 Paris Agreement would pose a substantial fiscal challenge. Reducing carbon dioxide emissions by 95% or more by 2050 would raise 7% (1-17%) of GDP in carbon tax revenue, half of current, global tax revenue. Revenues are relatively larger in poorer regions. Subsidies for carbon dioxide sequestration would amount to 6.6% (0.3-7.1%) of GDP. These numbers are conservative as they were estimated using models that assume first-best climate policy implementation and ignore the costs of raising revenue. The fiscal challenge rapidly shrinks if emission targets are relaxed.

econ.GN↗
arXiv2023

The climate niche of Homo Sapiens

I propose the Dominicy-Hill-Worton estimator to estimate the current climate niche of Homo Sapiens and our croplands. I use this to extrapolate the degree of unprecedentedness of future climates. Worton's peeled hull is a non-parametric, N-dimensional generalization of order statistics. Dominicy and colleagues show that Hill's estimator of the tail-index can be applied to any homogeneous function of multivariate order statistics. I apply the Dominicy-Hill estimator to transects through Worton's peels. I find a thick tail for low temperatures and a thin tail for high ones. That is, warming is more worrying than cooling. Similarly, wettening is more worrying than drying. Furthermore, temperature changes are more important than changes in precipitation. The results are not affected by income, population density, or time. I replace the Hill estimator by the QQ one and correct it for top-censoring. The qualitative results are unaffected.

physics.soc-ph↗
arXiv2023

Economic consequences of the spatial and temporal variability of climate change

Damage functions in integrated assessment models (IAMs) map changes in climate to economic impacts and form the basis for most of estimates of the social cost of carbon. Implicit in these functions lies an unwarranted assumption that restricts the spatial variation (Svar) and temporal variability (Tvar) of changes in climate to be null. This could bias damage estimates and the climate policy advice from IAMs. While the effects of Tvar have been studied in the literature, those of Svar and their interactions with Tvar have not. Here we present estimates of the economic costs of climate change that account for both Tvar and Svar, as well as for the seasonality of damages across sectors. Contrary to the results of recent studies which show little effect that of Tvar on expected losses, we reveal that ignoring Svar produces large downward biases, as warming is highly heterogeneous over space. Using a conservative calibration for the damage function, we show that previous estimates are biased downwards by about 23-36%, which represents additional losses of about US$1,400-US$2,300 billion by 2050 and US$17-US$28 trillion by the end of the century, under a high emissions scenario. The present value of losses during the period 2020-2100 would be larger than reported in previous studies by $47-$66 trillion or about 1/2 to 3/4 of annual global GDP in 2020. Our results imply that using global mean temperature change in IAMs as a summary measure of warming is not adequate for estimating the costs of climate change. Instead, IAMs should include a more complete description of climate conditions.

econ.GN↗
arXiv2023

Nobel begets Nobel

I construct the professor-student network for laureates of and candidates for the Nobel Prize in Economics. I study the effect of proximity to previous Nobelists on winning the Nobel Prize. Conditional on being Nobel-worthy, students and grandstudents of Nobel laureates are significantly less likely to win. Professors and fellow students of Nobel Prize winners, however, are significantly more likely to win.

econ.GN↗
arXiv2023

The Nobel Family

Nobel laureates cluster together. 696 of the 727 winners of the Nobel Prize in physics, chemistry, medicine, and economics belong to one single academic family tree. 668 trace their ancestry to Emmanuel Stupanus, 228 to Lord Rayleigh (physics, 1904). Craig Mello (medicine, 2006) counts 51 Nobelists among his ancestors. Chemistry laureates have the most Nobel ancestors and descendants, economics laureates the fewest. Chemistry is the central discipline. Its Nobelists have trained and are trained by Nobelists in other fields. Nobelists in physics (medicine) have trained (by) others. Economics stands apart. Openness to other disciplines is the same in recent and earlier times. The familial concentration of Nobelists is lower now than it used to be.

econ.GN↗
arXiv2023

The IPCC and the challenge of ex post policy evaluation

The IPCC started at a time when climate policy was an aspiration for the future. The research assessed in the early IPCC reports was necessarily about potential climate policies, always stylized and often optimized. The IPCC has continued on this path, even though there is now a considerable literature studying actual climate policy, in all its infuriating detail, warts and all. Four case studies suggest that the IPCC, in its current form, will not be able to successfully switch from ex ante to ex post policy evaluation. This transition is key as AR7 will most likely have to confront the failure to meet the 1.5K target. The four cases are as follows. (1) The scenarios first build and later endorsed by the IPCC all project a peaceful future with steady if not rapid economic growth everywhere, more closely resembling political manifestos than facts on the ground. (2) Successive IPCC reports have studiously avoided discussing the voluminous literature suggesting that political targets for greenhouse gas emission reduction are far from optimal, although a central part of that work was awarded the Nobel Prize in 2018. (3) IPCC AR5 found it impossible to acknowledge that the international climate policy negotiations from COP1 (Berlin) to COP19 (Warsaw) were bound to fail, just months before the radical overhaul at COP20 (Lima) proved that point. (4) IPCC AR6 by and large omitted the nascent literature on \textit{ex post} climate policy evaluation. Together, these cases suggest that the IPCC finds self-criticism difficult and is too close to policy makers to criticize past and current policy mistakes. One solution would be to move control over the IPCC to the national authorities on research and higher education.

econ.GN↗
arXiv2023

Navigating the energy trilemma during geopolitical and environmental crises

There are many indicators of energy security. Few measure what really matters -- affordable and reliable energy supply -- and the trade-offs between the two. Reliability is physical, affordability is economic. Russia's latest invasion of Ukraine highlights some of the problems with energy security, from long-term contracts being broken to supposedly secure supplies being diverted to retired power plants being recommissioned to spillovers to other markets. The transition to carbon-free energy poses new challenges for energy security, from a shift in dependence from some resources (coal, oil, gas) to others (rare earths, wind, sunshine) to substantial redundancies in the energy capital stock to undercapitalized energy companies, while regulatory uncertainty deters investment. Renewables improve energy security in one dimension, but worsen it in others, particularly long spells of little wind. Security problems with rare earths and borrowed capital are less pronounced, as stock rather than flow.

econ.GN↗
arXiv2023

Matlab routines for centrality in directed acyclic graphs

New Matlab functions for network centrality are introduced. Instead of the mean distance, the generalized mean distance is used. If closer relationships are prioritized, this closeness measure is also defined for unconnected graphs. Instead of distance to all nodes, distance to selected nodes is considered. Besides the vertical in- and out-closeness measures, horizontal cross-closeness is proposed.

stat.OT↗
arXiv2022

Costs and Benefits of the Paris Climate Targets

The temperature targets in the Paris Agreement cannot be met without very rapid reduction of greenhouse gas emissions and removal of carbon dioxide from the atmosphere. The latter requires large, perhaps prohibitively large subsidies. The central estimate of the costs of climate policy, unrealistically assuming least-cost implementation, is 3.8-5.6\% of GDP in 2100. The central estimate of the benefits of climate policy, unrealistically assuming constant vulnerability, is 2.8-3.2\% of GDP. The uncertainty about the benefits is larger than the uncertainty about the costs. The Paris targets do not pass the cost-benefit test unless risk aversion is high and discount rate low.

econ.GN↗
arXiv2022

A meta-analysis of the total economic impact of climate change

Earlier meta-analyses of the economic impact of climate change are updated with more data, with three new results: (1) The central estimate of the economic impact of global warming is always negative. (2) The confidence interval about the estimates is much wider. (3) Elicitation methods are most pessimistic, econometric studies most optimistic. Two previous results remain: (4) The uncertainty about the impact is skewed towards negative surprises. (5) Poorer countries are much more vulnerable than richer ones. A meta-analysis of the impact of weather shocks reveals that studies, which relate economic growth to temperature levels, cannot agree on the sign of the impact whereas studies, which make economic growth a function of temperature change do agree on the sign but differ an order of magnitude in effect size. The former studies posit that climate change has a permanent effect on economic growth, the latter that the effect is transient. The impact on economic growth implied by studies of the impact of climate change is close to the growth impact estimated as a function of weather shocks. The social cost of carbon shows a similar pattern to the total impact estimates, but with more emphasis on the impacts of moderate warming in the near and medium term.

econ.GN↗
arXiv2022

Estimates of the social cost of carbon have increased over time

A meta-analysis of published estimates shows that the social cost of carbon has increased as knowledge about climate change accumulates. Correcting for inflation and emission year and controlling for the discount rate, kernel density decomposition reveals a non-stationary distribution. In the last 10 years, estimates of the social cost of carbon have increased from $33/tC to $146/tC for a high discount rate and from $446/tC to $1925/tC for a low discount rate. Actual carbon prices are almost everywhere below its estimated value and should therefore go up.

econ.GN↗
arXiv2022

Confidence Intervals for Recursive Journal Impact Factors

We compute confidence intervals for recursive impact factors, that take into account that some citations are more prestigious than others, as well as for the associated ranks of journals, applying the methods to the population of economics journals. The Quarterly Journal of Economics is clearly the journal with greatest impact, the confidence interval for its rank only includes one. Based on the simple bootstrap, the remainder of the Top5 journals are in the top 6 together with the Journal of Finance, while the Xie et al. (2009), and Mogstad et al. (2022) methods generally broaden estimated confidence intervals, particularly for mid-ranking journals. All methods agree that most apparent differences in journal quality are, in fact, mostly insignificant.

econ.GN↗
arXiv2021

Probabilistic Projections of Baseline 21st Century CO$_2$ Emissions Using a Simple Calibrated Integrated Assessment Model

Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, global economic growth, and population growth, to make probabilistic projections of carbon emissions through 2100. Under a variety of assumptions about fossil fuel resource levels and decarbonization rates, our projections largely agree with several emissions projections under current policy conditions. Our global sensitivity analysis identifies several key economic drivers of uncertainty in future emissions and shows important higher-level interactions between economic and technological parameters, while population uncertainties are less important. Our analysis also projects relatively low global economic growth rates over the remainder of the century. This illustrates the importance of additional research into economic growth dynamics for climate risk assessment, especially if pledged and future climate mitigation policies are weakened or have delayed implementations. These results showcase the power of using a simple, transparent, and calibrated model. While the simple model structure has several advantages, it also creates caveats for our results which are related to important areas for further research.

stat.AP↗