Measurement of reciprocity in a village through social networks

ABSTRACT

This paper examines measuring of interdependency among households through their transactions by using information of individual villagers in a disadvantaged area in a developing country. To obtain the information, we created a village input–output table (VIOT) from household survey data conducted in a rural village in Lao PDR in 2015 and 2016. Because each household in the village is not only a producer but also a consumer who is trading products and consuming them, the VIOT is a simple but useful tool to know the economic transactions among villagers. The main findings are that four higher-income families, which mainly trade rice very frequently, are playing key roles in the village economy, and the interdependency among higher-income households is stronger than among lower/middle-income households. Additionally, this method can be used to form an economic policy such as poverty reduction because of informing households playing a key role in the village.

KEYWORDS:

• Qualitative input–output table
• interdependency among villagers
• economic developments
• cause of poverty appearance

Acknowledgements

We are grateful to anonymous referees and editors of the journal for their useful and constructive comments to revise this article.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 For more information regarding the serious problems with international financial support, see Deaton (2013) and Krueger (1998).

2 For more information on the influence of the political system and institutions on economic development, see Acemoglu and Robinson (2011).

3 Our VIOT is similar to an international or interregional IOT, i.e. an Isard-type, if one considers each household to play the role of a country or region (Hongsakhone et al., 2017).

4 Hamasuna (1996) tells us that Czayka's earliest work on qualitative input–output analysis.

5 For example, the multiplier of Japan’s IOT with 190 sectors is 2.00 in 2011 and 1.99 in 2005, which are both higher than that of the Phonxay VIOT. In general, however, a national IOT tends to have a higher multiplier than its regional counterparts because subregions tend to depend more on outside areas for trade, i.e. their commodity in- and outflows. For example, the multiplier of the Hiroshima IOT (2005) with 108 sectors is 1.40, and that of the Shizuoka IOT (2000) with 188 sectors is 1.30, both of which are lower than that of the Phonxay VIOT.

6 For more information about the qualitative input–output method, see Holub and Schnabl (1985) and Defourny and Thorbecke (1984). The application to economic analysis and the interpretations of this method are shown in Ichihashi (1995, 2004, 2007).

7 Our method is an application of directed graph and network theories from Clark and Holton (1991, Chapters 1 and 7), see also Miller and Blair (2009, Chapter 14). The basic theorem we use here is proven in the supplemental Appendix.

8 For the simplicity of our explanation, we use a simple matrix A here. This matrix can be easily transformed into the matrix reflected self-sufficient rates, but our explanation remains the same. Also, A can be replaced with the allocation coefficient matrix of the Ghosh model, but for our purposes, the traditional Leontief model is suitable. See Leontief (1986) for the classical input–output model, and see Dietzenbacher (1997) for interpretations of the Ghosh model.

9 Even if we assume a competitive import model, the result holds.

10 See Miller and Blair (2009 Chapters 2, 7, and 14) for power series approximation. In general, the summation of the power series estimation of the Leontief inverse by exponentiating matrix A up to the third round yields a result that is sufficiently close approximation to the Leontief inverse, that is it provides results that are 90% of all values. For example, the result of this calculation using Japan’s (2000) input–output table with 37 sectors converged to within 95% of the values in the Leontief inverse by the third round, and the calculation of the Asian (2000) input–output table with 70 sectors yielded values within 94% of those in the Leontief inverse by the third round (Ichihashi, 2007).

11 For example, our results show which households’ connectivity in the village or which networks are relatively small and weak, which could be used to inform policy-makers regarding which households should be financially supported and which households should be targeted by the marketing strategy. In addition, the results show which households are playing key roles in a village or a community, which would be also informative for policy-makers to think their development projects.

12 For the importance of skilled labor for economic development in a developing country, see Rahmaddi and Ichihashi (2013).

Additional information

Funding

This research was financially supported by a grant-in-aid from the Zengin Foundation for Studies on Economics and Finance in 2016 and Japan Society for the Promotion of Science (JSPS) KAKENHI [Grant Number JP16H05704].