Faculty of Economics

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Measures of physical mixing evaluate the economic mobility of the typical individual
(Elsevier BV, 2024-03)
Stojkoski, Viktor
Measures of economic mobility represent aggregate values for how individual wealth changes over time. As such, these measures may not describe the feasibility of a typical individual to change their wealth. To address this limitation, we introduce mixing, a concept from statistical physics, as a relevant phenomenon for quantifying how individuals move across the wealth distribution. We display the relationship between mixing and mobility both theoretically and using data. By studying the properties of an established model of wealth dynamics, we show that some individuals can move across the distribution when wealth is a non-mixing observable. Only in the mixing case every individual is able to move across the whole wealth distribution. There is also a direct equivalence between measures of mixing and the magnitude of the standard measures of economic mobility, but the opposite is not true. We then describe an empirical method for estimating the mixing properties of wealth dynamics in practice. We use this method to present a pedagogical application using the USA longitudinal data. This, approach, even though limited in data availability, leads to results suggesting that wealth in the USA is either non-mixing or that it takes a very long time for the individuals to mix within the distribution. These results showcase how mixing can be used in tandem with measures of mobility for drawing conclusions about the extent of mobility across the whole distribution.
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Estimating digital product trade through corporate revenue data
(Nature Communications, 2024-06-19)
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Koch, Philipp
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Coll, Eva
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Hidalgo, Cesar
Despite global efforts to harmonize international trade statistics, our understanding of digital trade and its implications remains limited. Here, we introduce a method to estimate bilateral exports and imports for dozens of sectors starting from the corporate revenue data of large digital firms. This method allows us to provide estimates for digitally ordered and delivered trade involving digital goods (e.g. video games), productized services (e.g. digital advertising), and digital intermediation fees (e.g. hotel rental), which together we call digital products. We use these estimates to study five key aspects of digital trade. We find that, compared to trade in physical goods, digital product exports are more spatially concentrated, have been growing faster, and can offset trade balance estimates, like the United States trade deficit on physical goods. We also find that countries that have decoupled economic growth from greenhouse gas emissions tend to have larger digital exports and that digital exports contribute positively to the complexity of economies. This method, dataset, and findings provide a new lens to understand the impact of international trade in digital products.
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Augmenting the availability of historical GDP per capita estimates through machine learning
(Proceedings of the National Academy of Sciences, 2024-09-16)
Koch, Philipp
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A. Hidalgo, César
Can we use data on the biographies of historical figures to estimate the GDP per capita of countries and regions? Here, we introduce a machine learning method to estimate the GDP per capita of dozens of countries and hundreds of regions in Europe and North America for the past seven centuries starting from data on the places of birth, death, and occupations of hundreds of thousands of historical figures. We build an elastic net regression model to perform feature selection and generate out-of-sample estimates that explain 90% of the variance in known historical income levels. We use this model to generate GDP per capita estimates for countries, regions, and time periods for which these data are not available and externally validate our estimates by comparing them with four proxies of economic output: urbanization rates in the past 500 y, body height in the 18th century, well-being in 1850, and church building activity in the 14th and 15th century. Additionally, we show our estimates reproduce the well-known reversal of fortune between southwestern and northwestern Europe between 1300 and 1800 and find this is largely driven by countries and regions engaged in Atlantic trade. These findings validate the use of fine-grained biographical data as a method to augment historical GDP per capita estimates. We publish our estimates with CI together with all collected source data in a comprehensive dataset.
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The role of immigrants, emigrants and locals in the historical formation of European knowledge agglomerations
(Informa UK Limited, 2023-11-27)
Koch, Philipp
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Hidalgo, César A.
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A first passage under resetting approach to income dynamics
(Elsevier BV, 2023-10)
Jolakoski, Petar
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Pal, Arnab
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Sandev, Trifce
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Metzler, Ralf
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Multidimensional economic complexity and inclusive green growth
(Springer Science and Business Media LLC, 2023-04-21)
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Koch, Philipp
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Hidalgo, César A.
<jats:title>Abstract</jats:title><jats:p>To achieve inclusive green growth, countries need to consider a multiplicity of economic, social, and environmental factors. These are often captured by metrics of economic complexity derived from the geography of trade, thus missing key information on innovative activities. To bridge this gap, we combine trade data with data on patent applications and research publications to build models that significantly and robustly improve the ability of economic complexity metrics to explain international variations in inclusive green growth. We show that measures of complexity built on trade and patent data combine to explain future economic growth and income inequality and that countries that score high in all three metrics tend to exhibit lower emission intensities. These findings illustrate how the geography of trade, technology, and research combine to explain inclusive green growth.</jats:p>
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Income Mobility and Mixing in North Macedonia
(Faculty of Economics-Skopje, Ss. Cyril and Methodius University in Skopje, 2023-12-15)
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Mitikj, Sonja
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This study presents the inaugural analysis of income mobility in North Macedonia from 1995-2021 using the Mixing Time and Mean First Passage Time (MFPT) metrics. We document larger mobility (in terms of Mixing Time) during the '90s, with and decreasing trend (in terms of mobility) until 1999. After this year the Mixing time has been consistent with a value of around 4 years. Using the MFPT, we highlight the evolving challenges individuals face when aspiring to higher income tiers. Namely, we show that there was a noticeable upward trend in MFPT from 1995 to 2006, a subsequent decline until 2017, and then an ascent again, peaking in 2021. These findings provide a foundational perspective on the income mobility in North Macedonia.
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The role of non-ergodicity in asset pricing, wealth dynamics, and income dynamics: Theoretical results and empirical applications
(2023-09-22)
How does randomness affect the evolution of an economy? The bedrock to answering this question lies in the ergodic hypothesis. Mathematically, the hypothesis tells us that an observable (e.g, the return of an asset or the growth rate of our wealth) is ergodic if its time average is equal to its expected value. Philosophically, if the hypothesis is valid, it means that randomness does not affect the dynamics of the system. That is, every asset traded on a stock market will exhibit similar prices over time, and in the long run investors will be indifferent about their investment decisions. Also, it will be irrelevant to track economic inequality, as the economy will not discriminate between individuals on the basis of their history: everyone will experience wealth and poverty during their life. A growing body of literature, however, questions the validity of the ergodic hypothesis in economics. Despite a decade of important advances on bridging the gap between theory and applications, it remains unclear how the randomness induced by non-ergodicity is manifested in economic systems. In this document, we expand the literature by developing frameworks for studying the role of non-ergodicity in asset pricing, wealth dynamics, and income dynamics. The framework for modelling asset prices can be used to predict empirical option values and offers a computationally inexpensive and efficiently tractable solution for tracking the non-ergodic dynamics of asset prices. The framework for non-ergodic wealth dynamics can be used to infer which part of the population is able to live a wealthy life. The framework for income dynamics can be used to understand whether socio-economic policies for redistributing income work in the long run. These results are used to provide the first measurements of economic mobility in the Macedonian economy. A shared feature of these frameworks is that they unify results from previous research into comprehensive methodologies that can easily address the question of ergodicity. By practically implementing the frameworks, the puzzles besetting the current economic formalism can be resolved in a natural and empirically testable way. Namely, they can be applied in various economics domains: from tailoring optimal investment strategies up to designing essential policy interventions.
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The impact of state capacity on the cross‑country variations in COVID‑19 vaccination rates
(Springer Nature, 2022-01-29)
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Jolakoski, Petar
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The initial period of vaccination shows strong heterogeneity between countries’ vaccinations rollout, both in the terms of the start of the vaccination process and in the dynamics of the number of people that are vaccinated. A predominant thesis for this observation is that a key determinant of the swift and extensive vaccine rollout is state capacity. Here, we utilize two measures that quantify different aspects of the state capacity: (i) the external capacity (measured through the soft power of the country) and (ii) the internal capacity (measured via the country’s government effectiveness) and provide an empirical test for their relationship with the coronavirus vaccination outcome in the initial period (up to 31st March 2021). By using data on 128 countries and a two-step Heckman approach, we find that the soft power is a robust determinant of whether a country has started with the vaccination process. In addition, the government effectiveness is a key factor that determines vaccine roll-out. Altogether, our findings are in line with the hypothesis that state capacity determines the observed heterogeneity between countries in the initial period of COVID-19 vaccines rollout. As such, they are a stark reminder for the need for transparent and fair global response regarding fair and equitable availability of vaccines to every country.
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Correlates of the country differences in the infection and mortality rates during the first wave of the COVID-19 pandemic: evidence from Bayesian model averaging
(Scientific Reports, 2022-05-02)
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Jolakoski, Petar
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Utkovski, Zoran
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The COVID-19 pandemic resulted in great discrepancies in both infection and mortality rates between countries. Besides the biological and epidemiological factors, a multitude of social and economic criteria also influenced the extent to which these discrepancies appeared. Consequently, there is an active debate regarding the critical socio-economic and health factors that correlate with the infection and mortality rates outcome of the pandemic. Here, we leverage Bayesian model averaging techniques and country level data to investigate whether 28 variables, which describe a diverse set of health and socio-economic characteristics, correlate with the final number of infections and deaths during the first wave of the coronavirus pandemic. We show that only a few variables are able to robustly correlate with these outcomes. To understand the relationship between the potential correlates in explaining the infection and death rates, we create a Jointness Space. Using this space, we conclude that the extent to which each variable is able to provide a credible explanation for the COVID-19 infections/mortality outcome varies between countries because of their heterogeneous features.

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