arXiv subjects

César A. Hidalgo

Publications and source records attributed to César A. Hidalgo.

25 records · Page 2Linked to original sources

arXiv2018

Shooting High or Low: Do Countries Benefit from Entering Unrelated Activities?

Countries tend to diversify their exports by entering products that are related to their current exports. Yet this average behavior is not representative of every diversification path. In this paper, we introduce a method to identify periods when countries enter unrelated products. We analyze the economic diversification paths of 93 countries between 1965 and 2014 and find that countries enter unrelated products in only about 7.2% of all observations. We find that countries enter more unrelated products when they are at an intermediate level of economic development, and when they have higher levels of human capital. Finally, we ask whether countries entering more unrelated products grow faster than those entering only related products. The data shows that countries that enter more unrelated activities experience a small but significant increase in future economic growth, compared to countries with a similar level of income, human capital, capital stock per worker, and economic complexity.

q-fin.GN↗

arXiv2017

729 new measures of economic complexity (Addendum to Improving the Economic Complexity Index)

Recently we uploaded to the arxiv a paper entitled: Improving the Economic Complexity Index. There, we compared three metrics of the knowledge intensity of an economy, the original metric we published in 2009 (the Economic Complexity Index or ECI), a variation of the metric proposed in 2012, and a variation we called ECI+. It was brought to our attention that the definition of ECI+ was equivalent to the variation of the metric proposed in 2012. We have verified this claim, and found that while the equations are not exactly the same, they are similar enough to be our own oversight. More importantly, we now ask: how many variations of the original ECI work? In this paper we provide a simple unifying framework to explore multiple variations of ECI, including both the original 2009 ECI and the 2012 variation. We found that a large fraction of variations have a similar predictive power, indicating that the chance of finding a variation of ECI that works, after the seminal 2009 measure, are surprisingly high. In fact, more than 28 percent of these variations have a predictive power that is within 90 percent of the maximum for any variation. These findings show that, once the idea of measuring economic complexity was out, creating a variation with a similar predictive power (like the ones proposed in 2012) was trivial (a 1 in 3 shot). More importantly, the result show that using exports data to measure the knowledge intensity of an economy is a robust phenomenon that works for multiple functional forms. Moreover, the fact that multiple variations of the 2009 ECI perform close to the maximum, tells us that no variation of ECI will have a performance that is substantially better. This suggests that research efforts should focus on uncovering the mechanisms that contribute to the diffusion and accumulation of productive knowledge instead of on exploring small variations to existing measures.

econ.GN↗

arXiv2017

The structural constraints of income inequality in Latin America

Recent work has shown that a country's productive structure constrains its level of economic growth and income inequality. Here, we compare the productive structure of countries in Latin America and the Caribbean (LAC) with that of China and other High-Performing Asian Economies (HPAE) to expose the increasing gap in their productive capabilities. Moreover, we use the product space and the Product Gini Index to reveal the structural constraints on income inequality. Our network maps reveal that HPAE have managed to diversify into products typically produced by countries with low levels of income inequality, while LAC economies have remained dependent on products related to high levels of income inequality. We also introduce the Xgini, a coefficient that captures the constraints on income inequality imposed by the mix of products a country makes. Finally, we argue that LAC countries need to emphasize a smart combination of social and economic policies to overcome the structural constraints for inclusive growth.

q-fin.GN↗

arXiv2016

Deep Learning the City : Quantifying Urban Perception At A Global Scale

Computer vision methods that quantify the perception of urban environment are increasingly being used to study the relationship between a city's physical appearance and the behavior and health of its residents. Yet, the throughput of current methods is too limited to quantify the perception of cities across the world. To tackle this challenge, we introduce a new crowdsourced dataset containing 110,988 images from 56 cities, and 1,170,000 pairwise comparisons provided by 81,630 online volunteers along six perceptual attributes: safe, lively, boring, wealthy, depressing, and beautiful. Using this data, we train a Siamese-like convolutional neural architecture, which learns from a joint classification and ranking loss, to predict human judgments of pairwise image comparisons. Our results show that crowdsourcing combined with neural networks can produce urban perception data at the global scale.

cs.CV↗

arXiv2016

The amenity space and the evolution of neighborhoods

Neighborhoods populated by amenities--such as restaurants, cafes, and libraries--are considered to be a key property of desirable cities. Yet, despite the global enthusiasm for amenity-rich neighborhoods, little is known about the empirical laws governing the colocation of amenities at the neighborhood scale. Here, we contribute to our understanding of the naturally occurring neighborhood-scale agglomerations of amenities observed in cities by using a dataset summarizing the precise location of millions of amenities. We use this dataset to build the network of co-location of amenities, or Amenity Space, by first introducing a clustering algorithm to identify neighborhoods, and then using the identified neighborhoods to map the probability that two amenities will be co-located in one of them. Finally, we use the Amenity Space to build a recommender system that identifies the amenities that are missing in a neighborhood given its current pattern of specialization. This opens the door for the construction of amenity recommendation algorithms that can be used to evaluate neighborhoods and inform their improvement and development.

physics.soc-ph↗

arXiv2016

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps.

cs.DL↗

arXiv2016

Pantheon 1.0, a manually verified dataset of globally famous biographies

We present the Pantheon 1.0 dataset: a manually verified dataset of individuals that have transcended linguistic, temporal, and geographic boundaries. The Pantheon 1.0 dataset includes the 11,341 biographies present in more than 25 languages in Wikipedia and is enriched with: (i) manually verified demographic information (place and date of birth, gender) (ii) a taxonomy of occupations classifying each biography at three levels of aggregation and (iii) two measures of global popularity including the number of languages in which a biography is present in Wikipedia (L), and the Historical Popularity Index (HPI) a metric that combines information on L, time since birth, and page-views (2008-2013). We compare the Pantheon 1.0 dataset to data from the 2003 book, Human Accomplishments, and also to external measures of accomplishment in individual games and sports: Tennis, Swimming, Car Racing, and Chess. In all of these cases we find that measures of popularity (L and HPI) correlate highly with individual accomplishment, suggesting that measures of global popularity proxy the historical impact of individuals.

physics.soc-ph↗