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Abstract

This chapter delves further into the problem of growth theory and what has previously been referred to as low- or high-level equilibrium traps. It is a technical chapter in the sense that we develop a conceptual model that links population, land, output, innovation, and uncertainty in a dynamic and stochastic way. We then establish some initial conditions and calibrations based on data available for Shandong and Hebei, and use Monte Carlo methods to run the model over a 500-year period intended to mimic the years 1400 through 1900. We argue that when risk is explicitly entered into a classical growth model, the resulting dynamics are highly fractional. This leads us to consider the idea of fractional poverty traps.

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Notes

  1. 1.

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    Lin, J.Y. (1995). Op Cit, page 270. Cf. Mark, page 177, Elvin , Mark. (1973). The Pattern of the Chinese Past. Stanford, Calif.: Stanford University Press.

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    See Sinha , (1973). Op Cit, fn 62, page 19.

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  31. 31.

    Hagen (1959). Op Cit, page 315.

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    Carter , M.R., and C.B. Barrett , (2006). The economics of poverty traps and persistent poverty : An asset-based approach. The Journal of Development Studies, 42(2), 178–199.

  33. 33.

    For origination of first, second, third, and fourth generation poverty measures see Carter and Barrett (2006), Op Cit. Figure 1, page 180. Carter and Barret were actually seeking to classify econometric approaches to measuring poverty traps . We are taking a few liberties in our discussion.

  34. 34.

    This is the approach used in Zhou, L ., and C.G. Turvey , (2015). Testing Asset Dynamics for Poverty Traps in Rural China. Canadian Journal of Agricultural Economics, 63(1), 129–162.

  35. 35.

    Systemic or covariate risks may affect large populations at a moment in time, e.g. floods or drought . These are also referred to as systemic risks.

  36. 36.

    Examples of how understanding risk, and measuring asset loss or famine for purpose of insurance see Chantarat , S., Barrett , C. B., Mude , A. G., & Turvey , C. G. (2007). Using weather index insurance to improve drought response for famine prevention. American Journal of Agricultural Economics, 89(5), 1262–1268

    and for an example of a fourth generation approach that measures resilience and asset dynamics with insurance in place, see Chantarat , S., Mude , A. G., Barrett , C. B., & Turvey , C. G. (2017). Welfare impacts of index insurance in the presence of a poverty trap . World Development, 94, 119–138.

  37. 37.

    This claim appears to be validated by Kumar , C. S., Turvey , C. G. , & Kropp , J. D. (2013). The impact of credit constraints on farm households: Survey results from India and China. Applied Economic Perspectives and Policy, 35(3), 508–527.

  38. 38.

    Barrett , C. B., and B.M. Swallow , (2006). Fractal poverty traps . World development, 34(1), 1–15.

  39. 39.

    Huang , P. (1985). Op Cit.

  40. 40.

    Perkins , D.H. (1969). Op Cit, pages 28–29.

  41. 41.

    The dynamic is close to Boulding ’s and other specifications. He measures the population above subsistence but also includes what he refers to as an improvement coefficient to capture technological change, and a scarcity coefficient to capture resilience. Boulding (1955). Op Cit, pages 199–201.

  42. 42.

    Perkins (1969). Op Cit, Mathematical Supplement, pages 79–84.

  43. 43.

    Lin, J.Y. (1995). Op Cit, page 271.

  44. 44.

    Huang (1985). Op Cit, Appendices B and C.

    Perkins , D. (1969). Op Cit.

  45. 45.

    Buck , J.L. (1930). Op Cit, page 425.

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Fu, H., Turvey, C.G. (2018). Low-Level Equilibrium and Fractional Poverty Traps. In: The Evolution of Agricultural Credit during China’s Republican Era, 1912–1949. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-76801-4_3

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