gravity models · Julian Hinz

Gravity Distances

Julian Hinz — Fri, 01 May 2020 00:00:00 +0000

Ratio of arithmetic over harmonic distances in 2000.

Gravity-consistent aggregate distances (harmonic, geometric and arithmetic mean) between countries and other geographical entities computed using nighttime lights data as weights. In most applications the use of the harmonic mean distance (theta = -1) is recommended. Similarly, often time-invariant distances are sufficient, e.g. those with weight from the year 2000.

Entities	Years	File	Size
Countries to countries	2000	distances_countries-countries_2000.rds	801 KB
		distances_countries-countries_2000.csvy.gz	1.3 MB
		distances_countries-countries_2000.dta.gz	1 MB
	1992 – 2012	distances_countries-countries_1992-2012.rds	16.7 MB
		distances_countries-countries_1992-2012.csvy.gz	26.7 MB
		distances_countries-countries_1992-2012.dta.gz	21.4 MB
EU NUTS 2 regions to EU NUTS 2 regions	2000	distances_eu_nuts2-eu_nuts2_2000.rds	2.5 MB
		distances_eu_nuts2-eu_nuts2_2000.csvy.gz	3.9 MB
		distances_eu_nuts2-eu_nuts2_2000.dta.gz	3.2 MB
EU NUTS 3 regions to EU NUTS 3 regions	2000	distances_eu_nuts3-eu_nuts3_2000.rds	55.7 MB
		distances_eu_nuts3-eu_nuts3_2000.csvy.gz	77.4 MB
		distances_eu_nuts3-eu_nuts3_2000.dta.gz	65.1 MB
US states to US states	2000	distances_usstates-usstates_2000.rds	42 KB
		distances_usstates-usstates_2000.csvy.gz	87 KB
		distances_usstates-usstates_2000.dta.gz	71 KB
	1992 – 2012	distances_usstates-usstates_1992-2012.rds	1.2 MB
		distances_usstates-usstates_1992-2012.csvy.gz	1.7 MB
		distances_usstates-usstates_1992-2012.dta.gz	1.6 MB
US states to countries	2000	distances_usstates-countries_2000.rds	419 KB
		distances_usstates-countries_2000.csvy.gz	669 KB
		distances_usstates-countries_2000.dta.gz	543 KB
	1992 – 2012	distances_usstates-countries_1992-2012.rds	8.7 MB
		distances_usstates-countries_1992-2012.csvy.gz	12.5 MB
		distances_usstates-countries_1992-2012.dta.gz	11.4 MB
US states to Canadian provinces	2000	distances_usstates-canprovinces_2000.rds	19 KB
		distances_usstates-canprovinces_2000.csvy.gz	42 KB
		distances_usstates-canprovinces_2000.dta.gz	35 KB
	1992 – 2012	distances_usstates-canprovinces_1992-2012.rds	612 KB
		distances_usstates-canprovinces_1992-2012.csvy.gz	887 KB
		distances_usstates-canprovinces_1992-2012.dta.gz	808 KB
Canadian provinces to Canadian provinces	2000	distances_canprovinces-canprovinces_2000.rds	3 KB
		distances_canprovinces-canprovinces_2000.csvy.gz	5 KB
		distances_canprovinces-canprovinces_2000.dta.gz	4 KB
	1992 – 2012	distances_canprovinces-canprovinces_1992-2012.rds	60 KB
		distances_canprovinces-canprovinces_1992-2012.csvy.gz	111 KB
		distances_canprovinces-canprovinces_1992-2012.dta.gz	101 KB
Canadian provinces to countries	2000	distances_canprovinces-countries_2000.rds	96 KB
		distances_canprovinces-countries_2000.csvy.gz	169 KB
		distances_canprovinces-countries_2000.dta.gz	137 KB
	1992 – 2012	distances_canprovinces-countries_1992-2012.rds	2.2 MB
		distances_canprovinces-countries_1992-2012.csvy.gz	3.2 MB
		distances_canprovinces-countries_1992-2012.dta.gz	2.9 MB
Norwegian municipalities to	2011	distances_norway_municipalities_gpwv4_2011.rds	4 MB
Norwegian municipalities (kommuner)		distances_norway_municipalities_gpwv4_2011.csvy.gz	5.9 MB
		distances_norway_municipalities_gpwv4_2011.dta.gz	5 MB

Note that EU NUTS regions include those of candidate countries as well as of the UK. US states include Washington, DC and Puerto Rico.

For more detailed data with thetas ranging from -2 to +1 the use of the R package gravity.distances is recommended.

If you need gravity distances between geographic entities not listed above that could also be of interest to other researchers, please send me an e-mail. Maybe we can work something out: mail@julianhinz.com

gravity.distances

Julian Hinz — Wed, 01 Aug 2018 00:00:00 +0000

The R package gravity.distances provides distances between geographic entities — such as countries, US states or Canadian provinces — that are consistent with the gravity equation in international economics.

To install the package in R, simply run the following commands:


install.packages("remotes")
remotes::install_github("julianhinz/gravity.distances")

For more details and usage examples check out the respective GitHub repositories:

R package: gravity.distances
Dataset repository: gravity.distances_data

PLAID: Product-Level AI-Derived Indicators Database for International Trade

Carsten Brockhaus — Thu, 16 Apr 2026 00:00:00 +0000

HS-6 level Rauch classifications reveal substantial heterogeneity within individual SITC headings.

Empirical trade research routinely relies on product-level indicators – whether goods are homogeneous or differentiated, perishable or durable, hazardous or benign – but existing classifications were built for older nomenclatures and have not kept pace with modern HS data. Mapping them forward through concordance tables introduces measurement error that is difficult to quantify and impossible to fix at the source.

PLAID takes a different approach. An ensemble of four frontier LLMs independently reads each HS 6-digit product description and classifies it, with majority voting across models and built-in uncertainty quantification through inter-model disagreement. The beta release (v0.1) provides six indicators across all seven HS revisions since 1992:

Rauch classification (organised exchange / reference priced / differentiated)
BEC end-use (capital / intermediate / consumption)
Economic perishability (five-class scale with half-life estimate)
Hazardous materials (GHS/IMDG dangerous goods flag)
Semiconductor content (microchip/IC presence)
3TG conflict minerals (tin, tantalum, tungsten, gold)

Each indicator is validated against external benchmarks where available and demonstrated to be empirically relevant through gravity applications. All data and code are open.

Website: plaid.julianhinz.com (mirror: trade.ifw-kiel.de/PLAID)

To Russia with Love? The Impact of Sanctions on Regime Support

Robert Gold — Thu, 12 Sep 2024 00:00:00 +0000

Sanctions impact on regional exports.

Do economic sanctions affect internal support of sanctioned countries’ governments? To answer this question, we focus on the sanctions imposed on Russia in 2014 and identify their effect on voting behavior in both presidential and parliamentary elections. On the economic side, the sanctions significantly hurt Russia’s foreign trade — with regional variance. We use trade losses caused by the sanctions as measure for regional sanctions exposure. For identification, we rely on a structural gravity model that allows us to compare observed trade flows to counterfactual flows in the absence of sanctions. Difference-in-differences estimations reveal that regime support significantly increases in response to the sanctions, at the expense of voting support of Communist parties. For the average Russian district, sanctions exposure increases the vote share gained by President Putin and his party by 13 percent. Event studies and placebo estimations confirm the validity of our results.

Firm-level Gravity with Fixed Effects

Uğur Aytun — Fri, 19 Apr 2024 00:00:00 +0000

This paper introduces a new method for estimating gravity equations at the firm level by leveraging both firm and country-level trade data. By constructing a flexible estimation strategy that accounts for firm-level and country-level characteristics, in particular for multilateral resistances at origin and destination, we offer a novel approach to measure the impact of policy changes such as tariffs, sanctions, etc., on trade flows. Through a series of simulations and replications of established firm-level gravity estimations, we validate the robustness of our methodology. Our findings not only contribute to the empirical trade literature by providing a more precise analytical tool but also have significant policy implications, highlighting the heterogeneous effects of economic policies on firms within and across countries.

The Ties that Bind: Geopolitical Motivations for Economic Integration

Julian Hinz — Wed, 01 Feb 2023 00:00:00 +0000

Evolution of the mean of Importance of bilateral relations of big (left) and small (b) countries in future agreement with an EIA partner country and non-partner countries around trade deal at t = 0.

Economic determinants of economic integration agreements have received ample attention in the economic literature. Political motivations for such agreements have been mostly studied as functions of domestic politics or in the context of conflict. In this paper the author suggests a different narrative. Economic integration may be used as an instrument of foreign policy, where political considerations influence the choice of contracting partners. He sketches a simple model that exhibits the proposed mechanism in which a big country chooses between alternatives for integration in terms of economic and political welfare gains, while a small country is indifferent between possible partners for integration. In the empirical part the author uses a novel dataset on political events to test the predictions of the model and finds evidence for the hypothesis that there is more to economic integration than “just trade”. Geopolitical considerations play a determining role in the choice of the contracting partner country and the depth of economic integration.

The View from Space: Theory-based Time-varying Distances in the Gravity Model

Julian Hinz — Sat, 15 Oct 2022 00:00:00 +0000

Aggregate distances over time (Exponents in generalized mean of -1 and 1). Commonly used time-invariant distances from Mayer and Zignago (2011) for comparison.

In this paper I use a general representation of the gravity model in international economics to derive a theory-consistent spatial aggregation of bilateral frictions. I apply the method to compute time-varying country-to-country distances, used in estimations of the gravity model in fields ranging from international trade, to foreign direct investment and migration. The aggregation takes the form of a weighted generalized mean, where the weights reflect the spatial distribution of economic activity in a country and the elasticity of the bilateral friction in question is a key parameter. I use annually available satellite imagery on nighttime light emissions for highly-detailed information on the economic geography of countries, capturing urban and rural areas and reflecting changes over time. Employing the computed distances in an application to the gravity equation of international trade yields a number of noteworthy results. Exploiting the time variation, I can estimate the distance elasticity while controlling for unobserved country-pair characteristics. Estimates for the distance coefficient are in the range of -0.5 and -1. Furthermore, the distances' use yields important consequences for estimates of other gravity variables: the border coefficient, i.e. the often puzzlingly large relative difference between internal and external trade, is reduced by between 30% and 50%. Regressions using simulated data confirm the theoretical and empirical findings.

Frictions to intranational investment

Inga Heiland — Wed, 01 Jul 2020 00:00:00 +0000

Despite unhalted technological progress in transport and communication infrastructure over the past century, geographical and cultural distance remain major obstacles to the flow of goods and production factors to date. In this paper, we show that geographical and cultural distance forcefully shape intranational investment flows in Norway, preventing an efficient allocation of capital to firms. To that end, we derive a structural gravity equation of investment from a general equilibrium model with multiple locations, multiple assets, and information frictions. Based on the model, we identify frictions related to geographical distance, travel time, administrative borders, and language differences and quantify the loss in terms of portfolio efficiency caused by each individual friction and by gravity as a whole. We also aim to study the impact of major infrastructure developments during the 2000s through the lens of the model: The politically-driven roll-out of broadband internet access across the country and the rapid expansion of the flight route network driven by Norwegian Airlines. Finally, we aim to deliver ex-ante predictions for the effects of a railway line connecting Northern Norway to the country’s main rail network, as well as the effects of a change to the speed limit on major road connections.

The Cost of Sanctions: Estimating Lost Trade with Gravity

Julian Hinz — Wed, 01 May 2019 00:00:00 +0000

Economic sanctions are a frequently used tool of foreign policy. Constraining trade ﬂows towards or from the target country is supposed to coerce its government into changing certain policies. However, sanctions constitute an obstacle to trade, thereby affecting ﬂows of all countries, including those of sanctioning countries themselves. I gauge the global impact of three recent sanctions regimes using a structural gravity framework and quantify the “lost trade” in a general equilibrium counterfactual exercise. Each of the episodes, sanctions against Iran, Russia and Myanmar, are instructive in their own way, due to the different nature of bilateral trade and severity of measures applied.