Archive for the ‘Economics’ Category

Up the ante on bioeconomic submodels of marine food webs

September 20, 2016

My new paper is available for free download for 50 days (until November 9, 2016). The paper is published in the journal Ecological Economics and discusses modeling of marine food webs such that economic analysis is viable. At the core of our approach lie the ensemble Kalman filter, something I have used earlier. In this new application, we go further in reducing model parameter dimensionality and move beyond the filtering routine to estimate certain structure parameters. We also apply a data transformation that deal with previously overlooked endogeneity in stock level data. We use all this to estimate a model of the largest pelagic fish stocks in the Norwegian Sea. The abstract:

eeWhile economists have discussed ecosystem-based fisheries management and similar concepts, little attention has been devoted to purposeful modeling of food webs. Models of ecosystems or food webs that make economic analysis viable should capture as much as possible of system structure and dynamics while balancing biological and ecological detail against dimensionality and model complexity. Relevant models need strong, empirical content, but data availability may inhibit modeling efforts. Models are bound to be nonlinear, and model and observational uncertainty should be included. To deal with these issues and to improve modeling of ecosystems or food webs for use in ecosystem-based fisheries management analysis, we suggest the data assimilation method ensemble Kalman filtering. To illustrate the method, we model the dynamics of the main, pelagic species in the Norwegian Sea. In order to reduce parameter dimensionality, the species are modeled to rely on a common carrying capacity. We also take further methodological steps to deal with a still high number of parameters. Our best model captures much of the observed dynamics in the fish stocks while the estimated model error is moderate.

The paper is part of the EINSAM project.

Technical Change as a Stochastic Trend in a Fisheries Model

June 3, 2016

Right, I have a couple of things forthcoming. One is, as the post-title suggests, on technical change in fisheries, where I, in my first sole-authored paper in five years, suggest a state space approach to measure technical change in fisheries. The approach is applied to data from the Norwegian Lofoten cod fishery, a data set that previously has been analyzed with other, more typical methods (linear regressions).

The paper has a long history. It started in 2008, when I was a visiting grad student at the economics department of the University of California, San Diego (UCSD). There, Dale Squires, who I am proud to call my friend, presented an analysis of the Lofoten data. During my visit to UCSD, I had spent considerable time studying state space models and the Kalman filter, and during Dale’s talk I wondered whether a state space model would do a better job in estimating technical change. Dale’s analysis was published in 2010, at a time when I already had acquired the data and had started to develop a model and an algorithm. In 2011, during a train trip, I started to get promising results. Progress was doomed to be slow, however, because the entire project was a side project that I only worked on in short stints every now and then. At some point in 2012, I nevertheless had a manuscript ready for submission. I sent it to the same journal where Dale’s analysis was published. After an interesting and instructive review-process, the manuscript was rejected. In the years that followed, the manuscript was sent to a handful of journals (the manuscript took various forms over the years; condensed into the letter-format at one point), but the verdict was always the same: rejection. Over these years, Dale, who I kept in touch with, was always optimistic and encouraging, suggesting alternative journals. Early in 2015, the manuscript was finally sent to Marine Resource Economics, where it was accepted after no less than three rounds of revisions. In the last round, I had to pull out my initial version, written more than three years earlier, and add discussion that was revised out at some point along the road but which obviously had its place. The manuscript was formally accepted early this year (2016), eight years after I had the initial idea.

Late in 2014, more than six years into the process, I had another idea for how to carry out the analysis. I decided to pursue this new idea in another side project. This spin-off project had much faster progress, and less than six months later, a letter-form manuscript was already rejected. After some further work, expanding the manuscript to the more typical article form, the manuscript was submitted again, and I am now awaiting its review. This much faster progress on the second side project is partly taken, by me, as evidence that I have become better at what I do. The lower degree of complexity is, of course, also an important factor in the progress.

‘Technical Change as a Stochastic Trend in a Fisheries Model’ will appear in Marine Resource Economics during the fall. The abstract reads as follows:

mreTechnical change is generally seen as a major source of growth, but usually cannot be observed directly and measurement can be difficult. With only aggregate data, measurement puts further demands on the empirical strategy. Structural time series models and the state space form are well suited for unobserved phenomena, such as technical change. In fisheries, technical advances often contribute to increased fishing pressure, and improved productivity measures are important for managers concerned with efficiency or conservation. I apply a structural time series model with a stochastic trend to measure technical change in a Cobb-Douglas production function, considering both single equation and multivariate models. Results from the Norwegian Lofoten cod fishery show that the approach has both methodological and empirical advantages when compared with results from the general index approach, which has been applied in the literature.

UPDATE: The article is now available here:
DOI: 10.1086/687931

Qualifications for an economist

September 25, 2015

In The Worldly Philosophers, Robert L. Heilbroner brings this quote from Keynes on the qualifications for an economist. I’ve posted parts of this before, but it is worth repeating:

The study of economics does not seem to require any specialized gifts of an unusual high order. Is it not, intellectually regarded, a very easy subject compared with the higher branches of philosophy or pure science? An easy subject, at which very few excel!  The paradox finds its explanation, perhaps, in that the master-economist must possess a rare combination of gifts. He must be mathematician, historian, statesman, philosopher – in some degree. He must understand symbols and speak in words. He must contemplate the particular in terms of the general, and touch abstract and concrete in the same flight of thought. He must study the present in the light of the past for the purpose of the future. No part of man’s nature of his institutions must lie entirely outside his regard. He must be purposeful and disinterested in a simultaneous mood; as aloof and incorruptible as an artist, vet sometimes as near the earth as a politician.

Stochastically Induced Critical Depensation and Risk of Stock Collapse

July 9, 2015

mreMy research team has published a paper in the latest issue of Marine Resource Economics (vol. 30, no. 3). The paper is called Stochastically Induced Critical Depensation and Risk of Stock Collapse and discusses how stochasticity induces depensation in fisheries models. We also develop a measure of stock collapse risk and apply it to a model with an optimal harvest rate. The abstract reads as follows:

This article investigates the risk of stock collapse due to stochastically induced critical depensation in managed fisheries. We use a continuous-time surplus production model and an economic model with downwardsloping demand and stock-dependent costs. First, we derive an optimal exploitation policy as a feedback control rule by applying the Hamilton-Jacobi-Bellman approach and analyze the effects of stochasticity on the optimal policy. Then, we characterize the long-term sustainable optimal state and estimate the risk of stock collapse due to stochastically induced critical depensation. We find that the optimal harvest policy in the stochastic setting is conservative at low stochasticity and approaches the myopic solution at high stochasticity. The risk of stock collapse is increasing with the stochasticity and decreasing with stock sizes.

Mathiness in Economics

June 9, 2015

In the Papers & Proceedings section of American Economic Review, Paul Romer* describes, after revealing formal errors in a couple of recent prestigious articles, what he calls the new equilibrium in economics:

[…] empirical work is science; theory is entertainment. Presenting a model is like doing a card trick. Everybody knows that there will be some sleight of hand. There is no intent to deceive because no one takes it seriously.

At a seminar I attended recently, there was debate about the concept of rationality in economics. It was pointed out that any behavior (in the given case discussed, but the claim holds more generally, if not fully) can be rationalized if just the model is rich enough. But then rationality becomes worthless because we cannot falsify it, to use a Popperian term. This may be to take it too far; one can set up a model for rational behavior and find conflicting behavior. While we cannot conclude that behavior was irrational, we can conclude that the model we not rich enough.

Romer discusses mathiness in economics further on his blog.

*Romer, PM (2015) Mathiness in the Theory of Economic Growth, American Economic Review: Papers & Proceedings 105(5): 89-93.

Quote of the Day

April 15, 2015

Such in reality is the absurd confidence which almost all men have in their own good fortune, that wherever there is the least probability of success, too great a share of it is apt to go to them […] of its own accord.

– Adam Smith, Wealth of Nations, Book IV, ch. 7, part I

Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price

February 14, 2015

EREAt the end of last year, my research team got a study accepted in Environmental & Resource Economics. Our long and unsexy title — Harvesting in a Fishery with Stochastic Growth and a Mean-Reverting Price — tells only part of the story (but as much as we could fit!): We study a fish harvest model in two stochastic state variables (stock and price), where the price further is mean-reverting. Perhaps the most important finding is our demonstration of the complexity that arises in relatively simple models. The complex behavior of the optimal solution that we observe is difficult to understand intuitively, something which gave us a hard time in the peer-review process. As it should be, I guess. Anyway, our abstract reads as follows:

We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and possibly harvest dependent. Optimal exploitation has nonlinear responses to the price signal and should be conservative at low levels of biological stochasticity and aggressive at high levels. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect when the biological uncertainty is larger. We further observe that resource exploitation should be conservative when the price reverts slowly to the mean. Simulations show that, in the long run, both the stock level and the exploitation rate are lower than in the deterministic solution. With a harvest-dependent price, the long-run price is higher in the stochastic system. The price mean reversion rate has no influence on the long-run solutions.

Economics of Climate Change: A Problem from Hell

February 13, 2015

The economics demigod Martin Weitzman recently published a review of William Nordhaus’ The Climate Casino: Risk, Uncertainty, and Economics for a Warming World, where he provides the following characterization of the climate change economics problem:

The economics of climate change is a problem from hell. Trying to do a benefit-cost analysis […] of climate change policies bends and stretches the capability of our standard economist’s toolkit up to, and perhaps beyond, the breaking point. First and foremost, disconcertingly large uncertainties are everywhere, including the most challenging kinds of deep structural uncertainties. The climate change problem unfolds over centuries and millennia, a long intergenerational human time frame that most people are entirely unaccustomed to thinking about. With such long time frames, discounting becomes ultra-decisive for [benefit-cost analysis], and there is much debate and confusion about which long-run discount rate should be chosen. Irreversibilities abound, including the very long residence lifetime of atmospheric CO2. To add to the challenge, costs of new carbon-free technologies are uncertain. More importantly, for global mean temperature changes much above about 2 [degrees] C, estimating damages is mostly educated guesswork with a distressingly wide error cone. The evaluation and aggregation of such damages add yet another significant layer of uncertainty; we are even unsure even about what form the “damages function” should take. Climate change due to high [greenhouse gas] levels involves nonnegligible tail risks of low-probability catastrophic outcomes, ranging from “known unknown” tipping points to the “unknown unknowns” of black-swan bad-feedback events that we cannot even imagine today.

Striking. The review was published in the Review of Environmental Economics and Policy.

Estimating Endangered Species Interaction Risk with the Kalman Filter

March 22, 2014

Crossposting from the Reconhub:

AJAETogether with my co-author Stephen Stohs, I recently published an article in the American Journal of Agricultural Economics. The main gist is that with rare events like endangered species interactions, the statistical information in yearly data sets is limited, and that data from several years provide better information for decision making. We provide a method that is based on the Kalman filter and that allow for observations unequally spaced  in time. The method also takes account of spatiotemporal effects. We discuss the particular case of leatherback turtle bycatch in a gillnet fishery in California and Oregon. The leatherback is an endangered species, and in order to reduce bycatch, extensive spatiotemporal closures was imposed on the fishery in 2000. Our analysis shows that the interaction risk likely was smaller than in the scenarios that motivated the closures. To discuss whether the closures were and are warranted, require further analysis, however. As we discuss in the concluding section, closures in California may lead to trade leakages such that the total effect on the leatherback turtle stock is unknown. And the value of the leatherback in the ecosystem, and the value of its mere existence, is unknown.

The abstract:

To address the tradeoff between biodiversity conservation in marine ecosystems and fishing opportunity, it is important to quantify the risk of endangered species interactions in commercial fisheries. We propose a Kalman filter suitable for rare events to estimate the endangered leatherback turtle take risk in the California drift gillnet fishery in the years 1990–2010, conditional on spatiotemporal factors that affect take rates. Results suggest interaction risk has remained stable, but with substantial variation over the spatiotemporal distribution of effort. Our methods might also apply to recreation demand analysis with rare event risk, or to applications involving irregularly spaced observations, like trade-level stock market data.

Zilberman Comments on Guns, Germs, and Steel by Jared Diamond

June 14, 2013

Guns, Germs, and Steel by Jared Diamond is on my to-read list (which of course grows faster than I read). David Zilberman, a professor here at UC Berkeley, has a nice comment on the economic principles which can be taken from Guns. Zilberman hails the book as ‘one of these rare classic books written during our lifetime,’ no small acclamation.

[…] Diamond’s book provides context to the recent economics of natural resources. Extraction of resources in the present without consideration of the future can be destructive. The challenge of sustainability and building institutions that allow for the resource base to survive and flourish in the long run. If we don’t plan for the future, the cost may be very high.

Allow me to paraphrase: If we don’t plan for the future, it might cost us the future!

An Inquiry Into The Human Prospect by Robert L. Heilbroner

June 1, 2013

The Giannini Library at UC Berkeley discarded a pile of books, and I picked up Heilbroner’s An Inquiry Into The Human Prospect. The book is old (1974; books discarded from libraries usually are), and much of the discussion feels dated. Other parts are still relevant. But, let me take it from the top.

AnInquiryIntoTheHumanProspectOn the first page, Heilbroner asks Is there hope for man? Heilbroner then lists three large problems which together makes his question pertinent: population growth, the spread of nuclear weapons, and environmental problems (including resource depletion, pollution, and climate change). All three problems are to different degrees still relevant today. Both population growth and environmental problems still pose threats on global scales. They are also, I think, largely viewed as connected. We still worry about nuclear weapons falling into the wrong hands, but the Armageddon-like prospect of nuclear war is not upon us like it must have been during the cold war.

Heilbroner is a careful writer, and before he plunges into his analysis, he discusses its validity:

The problem caused by the intrusion of subjective values into its inquiries has always troubled social science, which has struggled, without too much success, to attain the presumed “value free” objectivity of the natural sciences. Alas, this ambition fails into account that the position of the social science investigator differs sharply from that of the observer of the natural world. The latter may stage his reputation as he regards the stars through his telescope or the cells through his microscope, but he is not himself morally embedded in the field he scrutinizes. By contrast, the social investigator is inextricably bound up with the objects of his scrutiny, as a member of a group, a class, a society, a nation, bringing him with feelings of animus or defensiveness to the phenomena he observes. In a word, his position in society-not only his material position but his moral position-is implicated in and often jeopardized by the act of investigation, and it is not surprising, therefore, that we find behind the great bulk of social science arguments that serve to justify the existential position of the social scientist [pp. 22-23*].

Heilbroner moves on to point out that while the moral position of the analyst (himself) has potential implications for his analysis, the moral position of the reader has implications for how to comprehend the analysis. In the end, Heilbroner finds that his conclusions about the human prospect do not accord with his own preferences and interests.

Parts of the book is not as relevant today as it was when it was written. For example, a lengthy discussion of whether a socialist or capitalist society is better able to take on the challenges Heilbroner has identified is today only of academic interest. That the discussion builds upon the work of Freud and his followers makes it arcane in my eyes, but I am relatively short-sighted. An interesting remark, though, on the necessity of regarding the political aspect:

We live in an age in which the very capacity for socio-economic analysis marks us off from the past. We read with amusement or shock the historical prognoses of the classical historians or political philosophers, into which socio-economic dynamics do not enter at all ( for the very good reason that the relevant social systems had not yet evolved) and in which, instead, we find purely political predictions , usually of dynastic rise and fall, and so forth. But however more “scientific” our socio-economic method may seem by comparison, its omission of a political dimension is nonetheless crippling, even fatal, for a comprehension of the human prospect [p. 100].

In the following discussion, Heilbroner asserts that the nation-state must be ‘considered as the embodiment of purely political, as well as socio-economic, behavioral forces’ (p. 112). I am not sure I fully understand Heilbroner here, but his assertion made me think about all the different historical configurations of the map of Europe. Does his assertion have implications for observed political behavior when political borders change? Would it be possible to empirically test his assertion in some sense?

The problem of time discounting is much debated in the current climate change debate. Heilbroner puts it clear:

[The] devaluation of the future is generally considered to be an entirely rational response to the uncertainties of life. But if we apply this same calculus of “reason” to the human prospect, we face the horrendous possibility that humanity may react to the approach of environmental danger by indulging in a vast fling while it is still possible-a fling entirely justified by the estimation of present enjoyments over future ones. On what private, “rational” considerations, after all, should we make sacrifices now to ease the lot of generations whom we will never live to see [pp. 114 – 115]?

Heilbroner finds it difficult to believe the ‘contemporary industrial man’ is willing to make the necessary sacrifices (p. 115). While I have not discussed all parts of the analysis, much of it is as I said not so relevant today as it undoubtedly was in 1974, it is nonetheless clear that Heilbroner finds little support for a positive view on the future:

[W]ith the full spectacle of the human prospect before us, the spirit quails and the will falters. We find ourselves pressed to the very limit of our personal capacities, not alone in summoning up the courage to look squarely at the dimensions of the impending predicament, but in finding words that can offer some plausible relief in a situation so bleak [p. 136].

In fact, the only consolation Heilbroner can offer, is that the idea of Atlas, the Greek god which figures on the cover of the book and who bears ‘with endless perseverance the weight of the heavens in his hands’, springs from elements within us (pp. 143 – 144).

*Page numbers refer to the 1974 edition (paperback).

Marine Resource Economics Impact Factor

May 2, 2013

Today, I discovered the impact factor of Marine Resource Economics is above 1. The MRE impact factor has only been measured since 2009. It started out in the territory around 0.5, which I found agreed well with my perception of the quality and standing of the journal. 1 is kind of a watershed, as I understand it, and the difference between 0.9 and 1.1 is more significant than the difference between 1.0 and 1.2.  Now that MRE is above 1, it is in the territory of journals like the American Journal of Agricultural Economics and Land Economics. It still has a lower impact, but less significantly so.


Seminar at Berkeley

May 1, 2013

Today, I will present the project Ecosystem-Based Fisheries Management in the Barents Sea in the Environmental and Resource Economics seminar at the Department of Agricultural and Resource Economics at UC Berkeley. The abstract:

While bioeconomic analysis has advanced to where high-level ecosystem management is technically possible in terms of multidimensional, stochastic optimization, the sentiment that the underlying, biological models are of limited interest is omnipresent. The existing models cannot capture the observed ecosystem or foodweb dynamics. For viable optimization schemes to apply, models have been, and will have to be, relatively simple when compared to population dynamics models. There exist a crucial tradeoff between biological detail and stylized simplicity. Biologically detailed models have been promoted by biologists who want their models to replicate what they observe in nature, while stylized simplicity has been promoted by resource economists who want to analyze economic decisions. We aim to narrow the gap and cheapen the tradeoff. We develop a bioeconomic model of the ecosystem in the Barents Sea. The model is fitted with data assimilation methods and captures the observed dynamics in the ecosystem and the economy. Using stochastic optimization, we study numerical solutions of the model. Optimal, non-concave harvest profiles underline the importance of the ecosystem approach. In the extension of our project, we will study how solutions from our top-down, optimization approach perform in a high-dimensional, bottom-up, simulation approach.

The project is interdisciplinary and finds itself where paths (or trails, really) from economics, biology, ecology, applied mathematics, and statistics meet. Thus, it is at the outskirts of all those disciplines. It is a rather dark place. It remains to be seen whether we can shed some light around. But enough of the Nordic realism.

I find it difficult to present papers from the project because they belong in a setting which cannot be taken light upon. My presentation will therefor span at least two papers, with focus on how to build a biological model for ecosystem-based management which lends itself to subsequent bioeconomic analysis. To drive home the importance of getting the biology right, I will also discuss how we proceed with the bioeconomic analysis.


Picture credits: Philip Steven,



Some Observations From the Berkeley Bioeconomy Conference

April 13, 2013

I attended the Berkeley Bioeconomy Conference some time ago, and would like to relay some notes and observations. It was interesting, as I am not a regular of the bioeconomy research community. First of all, the term bioeconomy (seldom or never bioeconomics, notably) seems to mean the economics of biofuel. A couple of highlights:

  • A carbon tax in the US has become slightly less unlikely because of the huge budget deficit. A tax on carbon would generate a lot of revenue. So, the financial crisis still has positive effects on the climate. First, it slowed down economic growth. Now it can lead to a carbon tax in the US. Well, a carbon tax is at least not as unlikely as before, but still unlikely. A couple of further moments are that the budget deficit did not origin within the financial crisis, but the situation did become worse after the crisis hit. And, the crisis has probably had a number of negative effects on the climate as well, like switching to dirtier fuels and perhaps less public and private money for research.
  • If production of crops for biofuel  has adverse effects on food production and prices, it is difficult to pin down empirically (at least in one study from Brazil).
  • When one delves into sustainability, it could unleash an array of potential issues to worry about, of conceptual, theoretical, philosophical, and regulatory nature. One second thought, any issue one could delve into could unleash any number of issues of different natures, a part of the art of getting anything done in research is not to engage all at the same time perhaps.
  • Few places are as ideal as Brazil for biofuel production. If it does not work there, it will likely not work anywhere.
  • Is a non-parametric estimate the same as a spline?
  • Electricity generated from shale gas is cheaper than hydropower(?!), and it is better to use natural gas to make electricity than to run cars (electric cars have great milage).
  • Voting is not necessarily an efficient tool to decide upon labeling of genetically modified food; willingness to pay could be higher in the minority. How the issue is framed is also of importance (a lesson from Kahneman there).
  • Price volatility of fussil fuel correlates with the business cycle (it is demand driven). Volitility in biofuel does not correlate with the business cycle and hence a bad agricultural year (bad weather) could deepen a recession.
  • Tinbergen, apparently (revealing some holes in my background here), told us that one should have one policy instrument for each policy target. Is that really true? It is at least easy to imagine a policy instrument active (in lack of a better word) in several dimensions.

Fisheries Management Under Irreversible Investment: Does Stochasticity Matter?

April 7, 2013

In the latest issue of Marine Resource Economics (vol. 28, no. 1) I co-author an article together with colleagues at the Norwegian School of Economics. We explore what optimal management looks like when capital has to be managed as well as the fish stock. In fisheries, fleet investments are to some degree irreversible; fishing boats has little alternative use. While little has been written on the multidimensional decision problem of how large a fleet to own (the capital decision) and how much of it to use (the fishing decision), we also look at the effect of stochasticity. Things quickly become messy in these models as the number of potential scenarios is large. While it is manageable in our present case, I do not look forward to seeing further extensions. Or rather, I would love to see creative takes on analysis and presentations of high dimensional problems.

MREOur abstract:

We present a continuous, nonlinear, stochastic, and dynamic model for capital investment in the exploitation of a renewable resource. Both the resource stock and capital are treated as state variables. The resource owner controls fishing effort and the investment rate in an optimal way. Biological stock growth and the capital depreciation rate are stochastic in the model. We find that the stochastic resource should be managed conservatively. The capital utilization rate is found to be a nonincreasing function of stochasticity. Investment could be either higher or lower depending on the interaction between capital and the resource stock. In general, a stochastic capital depreciation rate has no strong influence on optimal management. In the long run, the optimal harvest for a stochastic resource becomes lower than the deterministic level.