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A multi-agent model of a low income economy: simulating the distributional effects of natural disasters

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Abstract

This paper develops an agent-based model of a stylized low income region in order to study the impact of natural disasters on population displacement, income, prices, and consumption with a focus on distributions and coping strategies of low income groups. Key features of the model include the integration of decentralized markets into a full economy in a spatially explicit way and the analysis of short-run adjustment processes. The model is calibrated to a low income region of rural agrarian Pakistan that faced severe floods in 2010. Dynamic adaptation by agents in response to falling income includes migrating and running down savings. Despite these consumption smoothing strategies, some low income groups are vulnerable to starvation. The paper showcases two hypothetical policy scenarios, a cash and a food transfer program, and tracks their effects on the welfare of low income groups in the economy.

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Notes

  1. See also Naqvi (2012b) and Naqvi and Rehm (2014).

  2. The tradeable good is assumed to have no minimum consumption level and therefore depends only on income with a low value of \(\bar{\alpha }_{G}\), the marginal propensity to consume the tradeable good.

  3. Endogenous risk preference is explored in Naqvi (2012a) in an extension of the SHELscape model.

  4. An agent-based framework incorporating spatial family networks and various determinants of migration are explored in Rehm (2012).

  5. See Appendix 2 for details on the normalized distance matrices.

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Acknowledgments

We would like to thank the editor and three anonymous referees, Duncan Foley, Robert Axtell, and conference participants at IEEE CIFEr, EEA, FMM, EAEPE, IIASA, and the Crisismappers for their feedback and comments. The usual disclaimer applies.

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Authors and Affiliations

  1. Vienna University of Economics and Business, Vienna, Austria

    Ali Asjad Naqvi

  2. Chamber of Labor, Vienna, Austria

    Miriam Rehm

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  1. Ali Asjad Naqvi
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Correspondence to Ali Asjad Naqvi.

Appendices

Appendix 1: List of symbols

See the Tables 5 and 6.

Table 5 Variables
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Table 6 Parameters
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Appendix 2: Distance matrix

Table 7 shows the normalized distance matrix used in the behavioral rules selling (Sect. 3.5) and migration (Sect. 3.6). The distance \(\chi \) between two locations is calculated using Dijkstra (1959)’s shortest distance algorithm on a network where the distance to self is assumed to be 0. Since the network is bi-directional, the distance matrix is square and symmetric; we only show the lower triangle here. Distances are normalized by the maximum distance in the matrix \((\bar{\chi })\). In the model layout shown in Fig. 10, this maximum distance is between Village 5 and Village 7. The normalized distances are thus \(\hat{\chi }=\chi /\bar{\chi }\).

Table 7 Normalized distance matrix
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Appendix 3: Sensitivity analysis

In order to assess the sensitivity of the model to various shock levels, we perform multiple simulation runs for food production shocks ranging from 50 to 75 % in steps of 5 %. Sensitivity bands are generated from 10 simulation runs per shock. The values of variables reported refer to one year after the shock (Fig. 20).

Fig. 20
figure 20

Sensitivity analysis. a Real income, b food prices, c percentage rural, d average wheat consumption, e average savings, f percentage starving, g consumption from savings, h proportion income saved, i consumption Gini

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Naqvi, A.A., Rehm, M. A multi-agent model of a low income economy: simulating the distributional effects of natural disasters. J Econ Interact Coord 9, 275–309 (2014). https://doi.org/10.1007/s11403-014-0137-1

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