The Gravity of Arms

Martínez‐Zarzoso, Inmaculada; Johannsen, Florian

doi:10.1080/10242694.2017.1324722

Cited by 24 publications

(13 citation statements)

References 39 publications

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“…This choice of covariates is in line with recent empirical (Akerman and Seim, 2014;Martinez-Zarzoso and Johannsen, 2017;Bove et al, 2018;Thurner et al, 2018) and theoretical (Garcia-Alonso and Levine, 2007) arms trade research. It builds on a modelling approach similar to the gravity equation, a very common parsimonious structure for the analysis of international trade flows (Disdier and Head, 2008;Ward et al, 2013;Head and Mayer, 2014;Egger and Staub, 2016).…”

Section: Exogenous Covariatessupporting

confidence: 72%

“…We will employ the former. Spatial econometric models are common in network analysis, refer for instance Leenders (2002), Franzese Jr and Hays (2007), Hays et al (2010), Metz and Ingold (2017), Silk et al (2017), Ba (2017) as well as the package tnam by Leifeld et al (2016). We follow a SEM (see LeSage and Pace, 2009) which is given by defining the error term u as…”

Section: Regression Modelmentioning

confidence: 99%

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Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Lebacher

Thurner

Kauermann

2019

Statistical Modelling

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In the paper we analyse dependence structures among international trade flows of major conventional weapons from 1952 to 2016. We employ a Network Disturbance Model commonly used in inferential network analysis and spatial econometrics. The dependence structure is represented by pre-defined weight matrices that allow for relating the arms trade flows from the network of international arms exchange. Several different weight matrices are compared by means of the AIC in order to select the best dependence structure. It turns out that the dependence structure among the arms trade flows is rather complex and can be represented by a specification that, simply speaking, relates each arms trade flow to all exports and imports of the sending and the receiving state. By controlling for explanatory variables we are able to show the influence of political and economic variables on the volume traded.

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Section: Exogenous Covariatessupporting

confidence: 72%

Section: Regression Modelmentioning

confidence: 99%

Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Lebacher

Thurner

Kauermann

2019

Statistical Modelling

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“…Edge‐Specific Distance Measures: Because of the strong empirical evidence that geographical distance is a relevant factor in trade (Disdier & Head, 2008), we control for the logarithmic distance between capital cities in kilometres (Gleditsch, 2013). In recent applications of the gravity model to arms trade (Akerman & Seim, 2014; Bove et al., 2018; Martinez‐Zarzoso & Johannsen, 2017; Thurner et al., 2019), it is argued that political distance measures in terms of regime dissimilarity must also be inserted in the gravity equation. We use the absolute difference of the polity IV index (Marshall, 2017) between two countries, ranging from 20 (highest ideological distance) to 0 (no ideological distance).…”

Section: Application To the Datamentioning

confidence: 99%

“…(2019) use a binary gravity model in order to explain the exchange of major conventional weapons (MCW) in a network context. Martinez‐Zarzoso and Johannsen (2017) rely on the framework of Helpman et al. (2008) to investigate the influence of economic and political variables on the so‐called extensive and intensive margin of MCW trade.…”

Section: Introductionmentioning

confidence: 99%

Censored Regression for Modelling Small Arms Trade Volumes and Its ‘Forensic’ Use for Exploring Unreported Trades

Lebacher

Thurner

Kauermann

2021

Journal of the Royal Statistical Society Series C: Applied Statistics

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In this paper, we use a censored regression model to investigate data on the international trade of small arms and ammunition provided by the Norwegian Initiative on Small Arms Transfers. Taking a network‐based view on the transfers, we do not only rely on exogenous covariates but also estimate endogenous network effects. We apply a spatial autocorrelation gravity model with multiple weight matrices. The likelihood is maximized employing the Monte Carlo expectation maximization algorithm. Our approach reveals strong and stable endogenous network effects. Furthermore, we find evidence for a substantial path dependence as well as a close connection between exports of civilian and military small arms. The model is then used in a ‘forensic’ manner to analyse latent network structures and thereby to identify countries with higher or lower tendency to export or import than reflected in the data. The approach is also validated using a simulation study.

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“…The recent works of Anderson and Yotov (2017); Yotov et al (2016); Helpman (2011); Bernhofen (2013) and Van Bergeijk and Brakman (2010) are the glaring instances of the growing theoretical literature on the gravity model of trade. The model has been widely used in many empirical fields; such as, the international migration (Beine, Bertoli, and Moraga 2016) , tourism (Santana-Gallego, Ledesma-Rodríguez, and Pérez-Rodríguez 2016), health care (Teow et al 2018), agriculture and livestocks (Atif, Haiyun, andMahmood 2017, Luo andTian 2017), international trade (Batra 2006, Edmonds, La Croix, and Li 2008, Irshad et al 2018, Erdey and Pöstényi 2017, Huot and Kakinaka 2007, Kahouli 2016, Rahman 2010, Narayan and Nguyen 2016, Gashi, Hisarciklilar, and Pugh 2016, Zhou, Li, and Lei 2019, Shahriar, Qian, and Kea 2019, Martínez-Zarzoso and Johannsen 2017, Kohl 2019 , and investment (Pericoli, Pierucci, and Ventura 2014, Chang 2014). The gravity model has, in this way, become a useful tool of international trade analysis.…”

Section: Introductionmentioning

confidence: 99%

The gravity model of trade

Shahriar

Kea

et al. 2019

RIC

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Purpose. The purpose of this study is to trace the theoretical developments of the gravity model of trade. The key question is: what are the dominant features of the development of the gravity trade model? Methodology. This research is conducted by employing a number of methods that include the historical, descriptive and analytical methods. The main contribution of this paper is to trace the historical and theoretical development phases of the gravity model. Findings. This study is a novel attempt in terms of the identification of the four distinctive phases of the development of the gravity model. This work would, therefore, expand the existing literature on the gravity model. We argue that the development of the gravity model is the outcome of many research efforts. A large body of literature has given the model a solid theoretical foundation. But there is no consensus about the proper econometric estimation methods of the model. The gravity model is significant both historically and analytically. It is a useful tool for the analysis of international trade. It has become a popular research device used by the researchers and policy makers around the world. The gravity is regarded as one of the most successful models in the literature of international economics. Originality. The original contributions of this paper lie in streamlining the consistent historical development of the gravity model over a longer period of time-frame, ranging from 1885 to 2018. Limitations and Implications. This work is theoretical aspects of the trade gravity model. Future researchers could overcome the limitations by combining the theoretical and empirical studies in a paper. This paper can help the future researchers in dealing with the broad body of literature of gravity model. Acknowledement. This study was supported by the National Natural Science Foundation of China (grants No.71673223 & 71473197), and a PhD scholarship from the China Scholarship Council (CSC). The first author would like to thank the CSC for the financial support. He also acknowledges the invaluable research advice and guidance received from Dr. Yoto V. Yotov, professor at the School of Economics of the Lebow College of Business at Drexel University, Philadelphia, USA. The authors are highly grateful to the anonymous reviewers, managing editor, and the editor-in chief for their kind help and critical comments on the earlier drafts of the paper. However, the authors are responsible for the contents and limitations of the study. They declared no conflict of interests.

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The Gravity of Arms

Cited by 24 publications

References 39 publications

Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Exploring dependence structures in the international arms trade network: A network autocorrelation approach

Censored Regression for Modelling Small Arms Trade Volumes and Its ‘Forensic’ Use for Exploring Unreported Trades

The gravity model of trade

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