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Risk Management and International Security

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Part of the book series: Advances in Japanese Business and Economics ((AJBE,volume 24))

Abstract

Economics of national security or international security is so immense a topic as to be intimidating. As in most of economics it has both positive and normative components. The goal of this chapter is to offer examples of both. Positive analyses, attempt to understand the economic origins of conflicts among nations and the economic foundations of success or failure in these conflicts.

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Notes

  1. 1.

    Such manifestations of the economic approach to conflict and peace have a considerable history, dating at least from Hobbes, Emmanuel Kant, Norman Angell the 1933 Nobel Peace Prize winner, and in recent days, J. Hirshleifer, H Grossman, E. Thompson and many others.

  2. 2.

    Analysts such as T. Schelling, C. Hitch and R. McKean, A. Enthoven, and S. Enke, and H. Kahn, or political scientist like B. Brodie, A. Wholstetter and many others were focused largely on how to support defenses against feared Soviet strength.

  3. 3.

    This refers to Fukuyama (1992).

  4. 4.

    State boundaries in Europe and Central Asia for example.

  5. 5.

    An important feature in this evolution has been the growing collective, public-good nature of most instances of security challenge. Accordingly, by a widely accepted corollary of the “logic of collective action” with increased globalization we should experience more unmanaged or mismanagement of international conflict, since no entity with effective enforcement power exists to act in the interest of the whole world of nations.

  6. 6.

    Prominent in this literature is Alesina et al. (2000), Blainey (1991), Findlay (1996), Garfinkel and Skaperdas (2000), Grossman (1998), Grossman and Mendoza (2001), Hirshleifer (1988, 1991, 2000), McGuire (1967), Powell (1999), Sandler (2000), Skaperdas (1992), Thompson (1974, 1979), Tullock (1974), Wittman (1991, 2000).

  7. 7.

    References include Bergstrom et al. (1985), Bhagwati and Srinivasan (1976), Hilman and Ngo (1983), Hirshleifer (1953, 1987), McGuire (1990, 2000, 2006a), McGuire and Becker (2006), McGuire and Shibata (1985), Shibata (1986), Williams and Wright (1991).

  8. 8.

    The role of alliances, or self-monitored international agreements among countries should be prominent in both these applications, and should be considered another central theme in evolution of security analyses of the past 50 years.

  9. 9.

    Depending on technology, and on wealth and its distribution, the competition for limited resources, limited and desirable geography, or access to foreign markets (for resource supplies an/or outlets for production), will cause tension and conflict among countries. Moreover, these sources of conflict will interact with the political organization of societies to determine how conflicts will be perceived and resolved—whether peacefully or by war, by production, trade, and investment, or war and conquest.

  10. 10.

    These distinctions were, we believe, first emphasized by Thompson (1974).

  11. 11.

    An example of such benefit might be that one could answer the question “Why do countries fight wars with each other?” Wars are expensive. “Wouldn’t it be wiser and much cheaper to bargain?” The loser of the war can afford a high payment and still be far better off than fighting and losing, while the winner could save the terrible expense of war by allowing itself to be “bought off.” Does it follow that wars are all fought because of a mutual mistake? Or because of lack of information?

  12. 12.

    As recognized as early as Immanuel Kant (1795) the system of governance influences how the costs and benefits of war versus peace are distributed among the citizenry of countries. It determines the costs of governance itself and thus the feasibility of conquest, suppression, exploitation etc. Kant and many authors since him have argued that autocratic organization favors war-conquer-exploit outcomes since an autocrat skims off the benefits from success without paying much in the way of the costs of failure.

  13. 13.

    As the saying goes no “big bucks on the sidewalk.”

  14. 14.

    For a more complete model see McGuire (2002b).

  15. 15.

    We could incorporate past saving and present borrowing in the constraint as \(M \le R - S + S + \beta\) where \(\beta\) stands for borrowing and \(S\) stands for past military stockpiles accumulated at \(t = 0\).

  16. 16.

    These decisions all occur in period 0. This assumption of rational calculation of benefits and costs ignores the entirely reasonable advantages a country may find in promising or committing to irrational action. The calculus of conquest and survival may be different when sequences of moves and commitments are allowed for the players. If conquest or submission is a gigantic game of international “chicken,” then the capacity credibly to offer another the choice between annihilation and submission may not be adequately represented by force duel or conflict success function (CSF). The place of CSF’s in making symmetric commitments may be a lot more complicated. But CSF’s (as in our linear case) are still crucial to outcomes determined by “naively rational extortion,” when not only “will power” but also a demonstrated capability to conqueror (not requiring actual application of force) may be necessary to evoke capitulation. For more see McGuire (2006a).

  17. 17.

    Thus a more complete formulation could represent \(B_{A} ( \cdot )\) by a present value of future tribute diminished each year by the effects of war i.e. by \(B_{A} [PV_{t = 1 \ldots \infty } \{ U_{V}^{t} (M_{V}^{t = 0} )\} ]\). We will postpone including this improvement for later research.

  18. 18.

    Borrowing and stockpiling will influence the relative importance of these two impediments to conquest.

  19. 19.

    So long as conquest is worth the cost and perfect international financial markets exist, an attacking country may be able to make up its resource shortfall by borrowing today and repaying out of the conquered surplus (if the attacker) in the future. Similarly, a defending country should be able to borrow the entire present value of its surplus over survival needs to defend itself against takeover and pay back loans from that surplus in the future. Total borrowings and past savings then would add to offense and defense capabilities.

    Adding these factors first alters the resources constraints. We incorporate past saving and present borrowing in the constraint as \(M_{j} \le R_{j} - S_{j} + S_{j} + \beta_{j}\) and \(\beta_{j} \le \beta_{j} (R_{j} - S_{j} )\) where \(\beta_{j}\) stands for borrowing which is limited by some present value function of future surpluses, \(\beta_{j} (R_{j} - S_{j} )\) which can be used to repay debts, and \(S\) stands for past military stockpiles accumulated at \(t = 0\). These constraints apply to both attacker and defender, \(j = (A,V)\).

    Next the equilibrium conditions change: now for Eqs. (2.2) and (2.3) there is no change for \(M_{V}^{ND}\), but for \(M_{V}^{NF}\). Equation (2.4) now becomes \(S_{A} + \beta_{A} + R_{A} - S_{A} - H_{V}^{A} (M_{V} ) = 0\), with a corresponding adjustment in Eq. (2.4).

    With perfect information in international markets, both attacker and defender could not simultaneously borrow these maxima, as the market might anticipate that only one of the loans would be repaid. This effect could be incorporated in the present value borrowing constraints \(\beta_{j} (R_{j} - S_{j} )\).

  20. 20.

    It may seem unnatural to assume, as the diagram does, that the benefits of conquest are independent of \(M_{V}\), since \(M_{V}\) (or maybe \(M_{V} + M_{A}\)) can be a good proxy for the destructiveness of war itself, and therefore reduce the present value of all future war spoils to the conqueror. This effect can be easily included by adding another quadrant to the diagram to show how the future surplus available to a conqueror (\(U_{V}^{FUTURE} = R_{V}^{FUTURE} - S_{V}^{FUTURE}\)) may depend on \(M_{V}\) and/or \(M_{A}\).

  21. 21.

    This terminology was suggested to me by Prof. Charles Anderton.

  22. 22.

    This section draws on McGuire (2000, 730–751), and on McGuire and Becker (2006) We have benefited from earlier discussions and correspondence with Gary Becker, Christopher Clague, Jack Hirshleifer, Leonard Mirman, Mancur Olson, Hirofumi Shibata, Todd Sandler, George Tolley, and Murray Wolfson.

  23. 23.

    Throughout, we employ the accepted concept of Kihlstrom and Mirman (1981) to define risk aversion (RA) in a multi-commodity world: locally first degree homogeneous utility functions are locally risk neutral; local decreasing returns to scale or diminishing marginal utility of income represents local risk aversion.

  24. 24.

    Why governments should be more adept at predicting/managing supply disruption is of course a crucial issue. For a current summary of alternative positions see Williams and Wright (1991, 410–51).

  25. 25.

    Such could include: (1) military to preparedness reduce the likelihood of trade disruption. (McGuire and Shibata 1985, 1988); (2) diversification of trading partners (McGuire and Becker 1994); (3) geographical dispersion of assets/factors-of-production across national borders (McGuire 1986); (4) insurance alliance formation to allow partners to exchange guaranties against disruptions or emergencies (Ihori and McGuire 2007, 2009).

  26. 26.

    These authors conclude (p. 323) stockpiling should limit embargo price rise to unit cost of storage divided by embargo frequency. With low embargo frequency, the price rise based on the stockpiling criterion may be greater than with no stockpiling.

  27. 27.

    Shibata (1986) concludes “that the smaller the storage costs and the degree of quality deterioration of the stockpile, the greater [the text reads “smaller” but the context make clear that “greater” is intended] the optimal amount of the stockpile. (p. 10) … And the smaller the domestic costs of (exports) X in terms of (imports) Y relative to international terms of trade, the greater the possibility of the stockpiling policy’s superiority over the protective policy.” (p. 14).

  28. 28.

    As the duration of the emergency trade disruption lengthens, this assumption of complete factor immobility becomes less and less realistic. In fact the duration of an emergency which requires advance preparation is just that over which factors of production are immobile!

  29. 29.

    For further discussion of this assumption, see Tolley and Wilman (1977) and Nichols and Zeckhauser (1977).

  30. 30.

    More realistically the utility function might differ between war and peace; some goods are simply more valued in war. To incorporate this idea calls for introducing state-dependent utility where the marginal rate of substitution (MRS)—i.e. relative value—between x and y shifts systematically, but elaboration along these lines is left for later.

  31. 31.

    For \(\pi < \pi^{0}\) the negative protection, i.e. \(y_{M} < 0\) could be desired, but this is eliminated by assumption.

  32. 32.

    Some may find the assumption of only one period (with outcome uncertain as between two contingencies) too unrealistic. See Sect. 2.4 below.

  33. 33.

    More varied, and realistic alternatives are analyses in McGuire (2000, 2005, 2006).

  34. 34.

    Note that Eq. (2.15) is out of sequence.

  35. 35.

    A good alternative to this assumption might be that stockpiles can be provided at an actuarially fair price. In this case we would write \(p_{S} = [(1 - \pi )/\pi ]p_{W}\).

  36. 36.

    In fact, if U is homothetic and stockpiling can be purchased at a “fair price” as in \(p_{S} = [(1 - \pi )/\pi ]p_{W}\), then as shown by McGuire and Becker (2006) for even the smallest chance of war/emergency, optimal stockpiling for adversity will always entail so much preparation that a reversal of utility positions results . That is, the optimal stockpile will be so great that utility is actually higher in the “bad” event, the emergency. The utility reversal result follows from the fact that fair insurance requires equalization of marginal utility of good y across contingencies; and homothetic utility, therefore, implies the stated reversal (McGuire 1991; McGuire and Becker 1994, 2006). The geometric depiction of the optimal stockpile with perfect insurance is similar to Fig. 2.3. In this case however, the price line for transforming \(x^{\omega }\) into \(y^{\pi }\) i.e. \(p_{S} = p_{W} (1 - \pi )/\pi\) is very steep at low risks of adversity indicating how very cheap it is to stockpile for a very unlikely event.

  37. 37.

    This assertion can be proven provided only that the utility function \(U(x,y)\) is not concave from above, i.e. that the country is risk neutral or risk averse, not risk preferring. See McGuire and Becker (2006).

  38. 38.

    This conclusion depends critically on independence of stockpile costs from chance of war.

  39. 39.

    As an alternative to (2.11), a repeated, “rolling”, two-period decision context might be used to analyze stockpiling and protection. In such a model the same question would arise of how to handle the effect—on the decision to stockpile itself—of goods stocked in the present for consumption in the future when those stores become available even if no emergency actually materializes in the future. One approach to this question is to assume that inherited stockpiles add to initial wealth, with the stockpile repeatedly chosen period after period in steady state equilibrium. This approach is followed by Tolley and Wilman (1977). But an assumption of inheritance of (possibly depreciated) stockpiles would only influence the solu by an income effect in the steady state. Therefore, it will not be explicitly modeled here. We could represent this assumption in Eq. (2.11)—with other terms in W unchanged—by chang \(U^{k}\) to:

    \(U^{k} \left[ {(\bar{x} - p_{D} y_{D} - p_{W} y_{M}^{k} - p_{S} y_{S} ),(\bar{y}_{S} + y_{D} + y_{M}^{k} )} \right]\).

    Here \(\bar{y}_{S}\) represents the inherited stockpiles from the previous rolling decision. Steady state consistency requires that \(y_{S}^{*} = \bar{y}_{S}^{*}\), i.e. requires that stockpiles chosen period after period be the same as inherited stockpiles.

  40. 40.

    The explanation of this slope is as follows: when one unit less of \(x\) is “stockpiled” \(\Delta x_{S} = - 1\), and two more units of \(x\) are allocated to internal production \(\Delta x_{D} = + 2\), the net effect is one less unit of \(x\)-consumption available during war; this generates in turn \(+ 2q\) units of \(y\) from the internal reallocation, but \(- t\) units of \(y\) from the stockpile; thus the slope \(\Delta y/\Delta x\) becomes \((2q - t)\).

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Appendix: Mutual Insurance Model

Appendix: Mutual Insurance Model

2.1.1 Analytical Framework

Here we will expand the analysis of a country’s preparation and response to an emergency disruption when it can purchase or sell insurance from a trusted alliance partner. That is, we select one of the alternative instruments examined in the previous sections of the chapter, to focus on incentives among allies. The results are neither obvious nor expected.

There are two partner countries in the alliances, country 1 and country 2. They are identical in preferences but may be heterogeneous in income and emergency costs. They do not provide an international public good. There is an intra-alliance mutual insurance market.

Assuming additively separable utility functions, country i’s expected utility is given by

$$W_{i} = (1 - \alpha )V(c_{i}^{A} ) + \alpha V(c_{i}^{B} ),$$
(2.24)

where \(W_{i}\) is expected welfare of country i, \(c_{i}\) is private consumption of country \(i\;(i = 1,2)\). \(c_{i}\) is subject to uncertainty. In state A, which occurs at the probability of \(1 - \alpha\), country i enjoys \(c_{i}^{A}\). In state B, which occurs at the probability of \(\alpha\), country i cannot enjoy \(c_{i}^{A}\) but can enjoy \(c_{i}^{B}\). \(\alpha\) indicates the probability of an economically disruptive production emergency or a ‘war’. Note that subscript i refers to the country. Country 1 may buy insurance from or sell insurance to 2.

Country i’s budget constraint in each state is given by

$$c_{i}^{A} = Y_{i} - ps_{i}$$
(2.25a)
$$\begin{aligned} c_{i}^{B} & = (1 - \pi_{i} )Y_{i} - ps_{i} + s_{i} \\ & {\kern 1pt} = c_{i}^{A} - \pi Y_{i} + s_{i} \\ \end{aligned}$$
(2.25b)

where \(Y_{i}\) is exogenously given (identical) national income of country i. \(\pi_{i} ({>}0)\) indicates the net fraction of resources lost for each dollar of private production during the period of contingency when a war or natural disaster actually occurs—resources lost by reason of being diverted to a war effort or being cut off because of disruptions in production activities, thus leaving \((1 - \pi_{i} )Y_{i}\) of production under contingency B. p is the price of insurance, and \(\pi\) is called the penalty ratio.

s is the insurance return in event of emergency with p the price of insurance. In other words, \(ps\) indicates a demanding or buying country’s premium paid to a supplying or selling country during state A. If \(s > 0\;( < 0)\), s represents the demand (supply) country’s return in event of state B with p the price of insurance, that is, the premium per dollar of insurance coverage. Country 1’s return \(s_{1}\) may be positive or negative with country 2’s return, \(s_{2}\), necessarily opposite in sign. It is also assumed that uncertainty is restricted to production so that the insurance premium paid by a buyer country to a seller country in state B is risk free and is not subject to the penalty ratio.

We assume that each government (or consumer) determines its insurance demand or supply, treating exogenous parameters \(\alpha ,\pi\) and insurance price p as given.

From Eqs. (2.25a) and (2.25b) we have

$$pc_{i}^{B} + \rho c_{i}^{A} = (1 - p\pi_{i} )Y_{i}$$
(2.26)

where \(\rho = 1 - p\). We assume \(p < 1\;(\rho > 0)\) to investigate a meaningful realistic problem. The price of insurance, p, also means the price of consumption in state B, while \(1 - p\) means the price of consumption in state A. Effective income in the left hand side of Eq. (2.26) evaluates emergency costs \(\pi_{i} Y_{i}\) using p, the price of consumption in state B.

Each country maximizes its expected welfare (2.24) subject to its budget constraint (2.26). The first order condition for each country’s optimization is given by

$$\alpha \rho V_{c}^{B} = p(1 - \alpha )V_{c}^{A}$$
(2.27)

where \(V_{c}^{A} \equiv dV/dc^{A} ,V_{c}^{B} \equiv dV/dc^{B}\). At the optimum, the marginal utility gain from allocation of an extra dollar to s (LHS of 2.27) just equals the expected marginal utility cost of that last dollar (RHS of 2.27). For simplicity subscript i in Eq. (2.27), referring to country i, is omitted and \(c_{i}\) is rewritten as c.

For example, consider the log-linear utility function

$$W = (1 - \alpha )\log c_{i}^{A} + \alpha \log c_{i}^{B}$$
(2.28)

Then the ordinary demand functions for \(c_{i}^{A} ,c_{i}^{B}\), and \(s_{i}\) are respectively given by

$$c_{i}^{A} = \frac{1 - \alpha }{1 - p}(1 - p\pi_{i} )Y$$
(2.29a)
$$c_{i}^{B} = \frac{\alpha }{p}(1 - p\pi_{i} )Y$$
(2.29b)
$$s_{i} = \frac{{1 - p - (1 - \alpha )(1 - p\pi_{i} )}}{p(1 - p)}Y$$
(2.29c)

Eq. (2.29c) implies that if

$$\frac{{p(1 - \pi_{2} )}}{{1 - p\pi_{2} }} > \alpha > \frac{{p(1 - \pi_{1} )}}{{1 - p\pi_{1} }}$$
(2.30)

then, \(s_{1} > 0 > s_{2}\); which is compatible with or consistent with mutual insurance.

From Eqs. (2.29a) and (2.29b), we also have

$$c_{i}^{B} - c_{i}^{A} = \frac{{(1 - p\pi_{i} )(\alpha - p)}}{p(1 - p)}Y$$
(2.31)

which is negative if \(p > \alpha\).

2.1.2 Compensated Demand Function

Let us define the following expenditure function:

$$\text{Min} E_{i} \equiv pc_{i}^{B} + \rho c_{i}^{A} \quad {\text{subject}}\;\;{\text{to }}W_{i} \ge \overline{W}_{i}$$

Since preferences are identical between countries, the functional form is also the same between them. Considering Eq. (2.26), we have as the expenditure function

$$E(W_{i} ,\alpha ,1 - p,p) = \tilde{E}(W_{i} ,\alpha ,\rho ,p) = (1 - p\pi_{i} )Y_{i}$$
(2.32)

From Eq. (2.32) expenditure function E will determine \(W_{i}\) as a function of income \(Y_{i}\), the probability of “war” \(\alpha\), the penalty ratio \(\pi_{i}\), and the price of insurance p.

By a variant of Shephard’s Lemma we know

$$\tilde{E}_{ip} \equiv \partial \tilde{E}(W_{i} ,\alpha ,\rho ,p)/\partial p = c^{B} (W_{i} ,\alpha ,\rho ,p)$$
(2.33)
$$\tilde{E}_{i\rho } \equiv \partial \tilde{E}(W_{i} ,\alpha ,\rho ,p)/\partial \rho = c^{A} (W_{i} ,\alpha ,\rho ,p)$$
(2.34)
$$E_{ip} \equiv \partial E(W_{i} ,\alpha ,1 - p,p)/\partial p = c_{i}^{B} - c_{i}^{A} = s(W_{i} ,\alpha ,1 - p,p,\pi ,Y_{i} ) - \pi_{i} Y_{i}$$
(2.35)

where \(s(\;)\) is the compensated demand (or supply) function for insurance and \(c^{j} (\;)\) is the compensated demand function for private consumption in state \(j\;(j = A,B)\). It follows from Eq. (2.35) that \(s_{\pi } \equiv \partial s/\partial \pi Y = 1\).

Alternatively, from Eqs. (2.24) and (2.26), we solve for \(s,c^{A}\) and \(c^{B}\) respectively as functions of W and p, which give the compensated demand (or supply) functions for s, \(c^{A}\) and \(c^{B}\); Eqs. (2.35), (2.33) and (2.34), respectively.

Totally differentiating (2.24) and (2.26), yields

$$\left[ {\begin{array}{*{20}c} {\alpha \rho V_{c}^{B} /p,} & {\alpha V_{c}^{B} } \\ { - p(1 - \alpha )V_{cc}^{A} ,} & {\rho \alpha V_{cc}^{B} } \\ \end{array} } \right]\left[ {\begin{array}{*{20}c} {dc^{A} } \\ {dc^{B} } \\ \end{array} } \right] = \left[ {\begin{array}{*{20}c} 1 \\ 0 \\ \end{array} } \right]dW + \left[ {\begin{array}{*{20}c} 0 \\ {\alpha V_{c}^{B} /p} \\ \end{array} } \right]dp$$
(2.36)

where \(V_{cc}^{A} \equiv d^{2} V^{A} /dc^{A} dc^{A} ,V_{cc}^{B} \equiv d^{2} V^{B} /dc^{B} dc^{B} ,V^{A} \equiv V(c^{A} ),V^{B} \equiv V(c^{B} )\).

Hence we have

$$c_{W}^{A} \equiv \partial c^{A} /\partial W = \rho \alpha V_{cc}^{B} /\gamma > 0$$
(2.37)
$$c_{W}^{B} \equiv \partial c^{B} /\partial W = p(1 - \alpha )V_{cc}^{A} /\gamma > 0$$
(2.38)
$$s_{W} \equiv \partial s/\partial W = c_{W}^{B} - c_{W}^{A} = \left[ {p(1 - \alpha )V_{cc}^{A} - \alpha \rho V_{cc}^{B} } \right]/\gamma$$
(2.39)
$$\begin{aligned} E_{W} & \equiv \partial E/\partial W = p\partial c^{B} /\partial W + \rho \,\partial c^{A} /\partial W \\ & = \left[ {p^{2} (1 - \alpha )V_{cc}^{A} + \rho^{2} \alpha V_{cc}^{B} } \right]/\gamma = \frac{p}{{\alpha V_{c}^{B} }} > 0 \\ \end{aligned}$$
(2.40)
$$c_{p}^{A} \equiv \partial c^{A} /\partial p = - \alpha^{2} V_{c}^{B} V_{c}^{B} /p\gamma > 0$$
(2.41)
$$c_{p}^{B} \equiv \partial c^{B} /\partial p = \alpha^{2} V_{c}^{B} V_{c}^{B} \rho /p^{2} \gamma < 0$$
(2.42)
$$s_{p} \equiv \partial s/\partial p = c_{p}^{B} - c_{p}^{A} = \alpha^{2} V_{c}^{B} V_{c}^{B} /p^{2} \gamma < 0$$
(2.43)

where \(\gamma \equiv \alpha V_{c}^{B} \left[ {p^{2} (1 - \alpha )V_{cc}^{A} + \rho^{2} \alpha V_{cc}^{B} } \right]/p < 0\).

Greater values of W require higher values of \(c^{A} ,c^{B}\), and E. An increase in p raises \(c^{A}\) but reduces \(c^{B}\) and s—results that are qualitatively plausible. However, the sign of Eq. (2.43) is ambiguous. To see this, suppose relative risk aversion is constant \(\left( {\frac{{cV_{cc} }}{{V_{c} }} = - \lambda } \right)\). Then considering the first-order condition (2.26), (2.43) may be rewritten as

$$s_{W} = \alpha \rho \lambda V_{c}^{B} (c^{A} - c^{B} )/c^{A} c^{B} \gamma$$
(2.43′)

Thus, if \(c^{A} > c^{B}\), as we will assume then it follows that \(s_{W} < 0\) and \(E_{p} \equiv \partial E/\partial p = c^{B} - c^{A} < 0\). In summary, in so far as \(\pi_{1} Y_{1} \ge \pi_{2} Y_{2}\) and \(Y_{1} \le Y_{2}\) (and strict inequality obtains for one or both), then \(W_{1} < W_{2}\) and \(s_{1} > s_{2}\).

2.1.3 Two Country Model

The two country model will then be summarized by

$$E(W_{1} ,p) = (1 - p\pi_{1} )Y_{1}$$
(2.44)
$$E(W_{2} ,p) = (1 - p\pi_{2} )Y_{2}$$
(2.45)
$$s(W_{1} ,p,\pi_{1} Y_{1} ) + s(W_{2} ,p,\pi_{2} Y_{2} ) = 0$$
(2.46)

Equation (2.44) gives expected welfare of country 1 as a function of insurance price, p, and its own effective income, \((1 - p\pi_{1} )Y_{1}\). Similarly, Eq. (2.45) shows expected welfare of country 2. Equation (2.46) gives the equilibrium condition for the private mutual insurance market and shows the equilibrium value of insurance price, p. Since there are no externalities, this equilibrium is Pareto efficient.

The benefits of insurance-alliance formation depend crucially on the nature of relative risks of emergency. Equation (2.46) implies that \(s_{1}\) and \(s_{2}\) must have opposite signs. Without loss of generality, assume \(s_{1} > 0\) and \(s_{2} = - s_{1} < 0\). Then, country 1 is the buyer, while country 2 is the seller or writer of insurance. If \(Y_{1} = Y_{2}\) and \(\pi_{1} = \pi_{2}\), both countries are identical whence \(W_{1} = W_{2}\) and \(s_{1} = s_{2} = 0\). Accordingly, heterogeneous income and/or penalty ratios are essential for the mutual insurance. We now briefly explore how such a situation would occur.

Suppose that Y is the same between two countries. Nevertheless, if \(\pi\) is high in country 1 and low 2, it is still possible to have mutual insurance. With \(s_{\pi } = 1\), \(s_{i}\) is necessarily increasing with \(\pi_{i}\). Therefore, when \(\pi_{1} > \pi_{2}\), it is possible for \(s_{1} = - s_{2} > 0\). From Eqs. (2.44) and (2.45) we then would know \(W_{1} < W_{2}\) when \(\pi_{1} > \pi_{2}\).

2.1.4 Comparative Statics

Next we investigate some comparative statics results in this insurance model. Totally differentiating Eqs. (2.44), (2.45) and (2.46), gives

$$\left[ {\begin{array}{*{20}c} {E_{1W} } & 0 & {s_{1} } \\ 0 & {E_{2W} } & {s_{2} } \\ {s_{1W} } & {s_{2W} } & {s_{1p} + s_{2p} } \\ \end{array} } \right]\left[ {\begin{array}{*{20}c} {dW_{1} } \\ {dW_{2} } \\ {dp} \\ \end{array} } \right] = \left[ {\begin{array}{*{20}c} { - pY_{1} } \\ 0 \\ { - Y_{1} } \\ \end{array} } \right]d\pi_{1}$$
(2.47)

Hence, we have

$$\frac{{dW_{1} }}{{d\pi_{1} }} = - \frac{{Y_{1} }}{\Delta }\left\{ {p\left[ {E_{2W} (s_{1p} + s_{2p} ) - s_{2} s_{2W} } \right] - s_{1} E_{2W} } \right\}$$
(2.48)
$$\frac{{dW_{2} }}{{d\pi_{1} }} = - \frac{{Y_{1} }}{\Delta }s_{2} (ps_{1W} - E_{1W} )$$
(2.49)
$$\frac{dp}{{d\pi_{1} }} = \frac{Y}{\Delta }E_{2W} (ps_{1W} - E_{1W} )$$
(2.50)

where \(\Delta \equiv E_{1W} E_{2W} (s_{1p} + s_{2p} ) - s_{1} E_{2W} s_{1W} - s_{2} E_{1W} s_{2W}\) and the first subscript on the partial derivatives refers to the country. As shown in Eqs. (2.40) and (2.43), \(E_{W} > 0,s_{p} < 0\). Moreover, \(\Delta\) is negative from the stability condition.

Therefore, it is easy to see that Eq. (2.50) is positive. To see this note that an increase in \(\pi_{1}\) raises the price of insurance, p; an increase in the penalty ratio will raise the price of insurance. Since \(s_{2} < 0\), Eq. (2.49) is positive. An increase in p, of course, is desirable for the seller country; and an increase in \(\pi_{1}\) has a positive welfare spillover into country 2—this being the ordinary price effect. Since \(s_{1} > 0\), the sign of Eq. (2.48) is negative. An increase in \(\pi_{1}\), therefore, directly reduces the expected income of country 1—this being the ordinary the income effect. As country 1 is a buyer, an increase in p implies an unfavorable price effect, which will strengthen the unfavorable income effect of the increase in the penalty ratio. In sum then, an increase in \(\pi_{1}\) hurts country 1, while it benefits country 2.

An increase in \(\pi_{2}\) may be analyzed in the similar way. That is, it also increases the price of insurance, hurting country 1 due to the price effect. On the other hand, while greater \(\pi_{2}\) directly reduces country 2’s own effective income, it indirectly raises 2’s welfare due to the price effect. Since the latter price effect offsets the former income effect, the overall welfare effect on country 2 is ambiguous.

These results suggest that an increase in the emergency cost has different spillover effects, depending on where it occurs. If the penalty ratio rises in the demand country, it has a positive spillover effect on the supply country. On the other hand, if the penalty ratio rises in the supply country, it has a negative spillover effect on the demand/buying country. The reason here is that an increase in the penalty ratio in either country will raise the price of insurance. All these theoretical results seem intuitively and practically plausible.

Note particularly that a decrease in \(\pi_{i}\) has the same qualitative effect as an increase in \(Y_{i}\), national income of country i, by reducing the price of insurance. Although the penalty ratio does not directly affect the price of insurance changes in that ratio will affect the economy by changing emergency costs. Therefore, an increase in \(Y_{1}\) (income of the insurance buyer) will hurt country 2, while an increase in \(Y_{2}\) (income of the seller of insurance) benefits country 1. Each country directly gains from its own economic growth due to the income effect but country 2 gets smaller benefits of its own economic growth than country 1 due to a reduction in the price of the insurance that it sells. A surprising and underappreciated result that follows: World-wide economic growth is more beneficial to the country that buys insurance than it may be to the country that provides or sells it.

This structure of benefits and costs next leads us to analyze the effect of transferring income between the countries within our alliance. An income transfer like this is equivalent to a change in the penalty ratios: where the penalty ratio rises in one country but it decreases in another country. To capture this idea let the constraint of \(dY_{1} + dY_{2} = 0\). Then from Eqs. (2.44), (2.45) and (2.46) we have

$$\frac{{dW_{1} }}{{dY_{1} }} = \frac{1}{\Delta }\left[ {(1 - p\pi_{1} )E_{2W} (s_{1p} + s_{2p} ) + (\pi_{2} - \pi_{1} )s_{1} (ps_{2W} - E_{2W} )} \right]$$
(2.51)
$$\frac{{dW_{2} }}{{dY_{2} }} = - \frac{1}{\Delta }\left[ {(1 - p\pi_{2} )E_{1W} (s_{1p} + s_{2p} ) - (\pi_{2} - \pi_{1} )s_{2} (ps_{1W} - E_{1W} )} \right]$$
(2.52)
$$\frac{dp}{{dY_{1} }} = \frac{1}{\Delta }\left[ { - (1 - p\pi_{1} )s_{1W} E_{2W} + (1 - p\pi_{2} )s_{2W} E_{1W} + (\pi_{2} - \pi_{1} )E_{1W} E_{2W} } \right]$$
(2.53)

These equations lay bare the relationships among differences between countries in loss from emergency, \(\pi\), value of p the price of insurance, and welfare consequences of income/wealth transfer. Equation (2.53) implies that as \(\pi_{2} > \pi_{1}\), then p must be of a lower value and vice versa. That is, if the penalty ratio is higher in country 1, a transfer from country 2 to country 1 will raise the price of insurance, hurting the country that buys and benefiting the supplier country. This impact represents the price effect. As for income effect from greater \(\pi\), the buyer country gains and the supplying country loses. Thus, Eq. (2.51) is positive if \(\pi_{2} > \pi_{1}\). In this case both income and price effects benefit buyer country 1. However, if \(\pi_{1} > \pi_{2}\), the price effect of higher “p” hurts country 1, while the income effect benefits that country. Equation (2.51) becomes positive when the income effect dominates the price effect.

Equation (A29) is negative if \(\pi_{2} > \pi_{1}\). In that case both the income and price effects hurt country 2 the seller or writer of insurance. However, if \(\pi_{1} > \pi_{2}\), the sign of Eq. (A29) becomes ambiguous since the income and price effects offset each other. To sum up, when \(\pi_{2} > \pi_{1}\), the country which receives a transfer becomes better off while the country which pays out the transfer becomes worse off. However, if \(\pi_{2} < \pi_{1}\), we could have a transfer paradox: namely that a giving country gains and a receiving country loses.

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Ihori, T., McGuire, M., Nakagawa, S. (2019). Risk Management and International Security. In: International Governance and Risk Management. Advances in Japanese Business and Economics, vol 24. Springer, Singapore. https://doi.org/10.1007/978-981-13-8875-0_2

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