The Logic of Social Impact Analysis B. Essama-Nssah World Bank Poverty Reduction Group April 2007.

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Transcript of The Logic of Social Impact Analysis B. Essama-Nssah World Bank Poverty Reduction Group April 2007.

The Logic of Social Impact Analysis

B. Essama-Nssah

World Bank Poverty Reduction Group

April 2007

22

Introduction

• Fundamental Question of Development Effectiveness:

– Is the intervention having the intended effect on the target population?

• Goal of intervention defines the metric for effectiveness

– Aristotelian vision: Maintaining and improving the living standard of the population is the ultimate goal of public policy and a fundamental expectation of the governed (Sen et al. 1987).

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Introduction

• Working Definition

– Social impact analysis is an assessment of variations in individual and social welfare attributable to a shock or the implementation of a socioeconomic policy.

• Hence PSIA is an exercise in social evaluation

– Evaluation: assessment of relative merits of actions.

– Valuation: comparison of things.

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Introduction

• Evaluative Framework

– Identification of objects of value and stakeholders.

•On the basis of the policy objective.

– Aggregation

• Linking individual and social outcomes

– Attribution

•To what extent is the outcome induced by intervention?

– Ranking

•Based on welfare maximization

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Introduction• Focus of Presentation

– The Living Standard

•Welfarism

•Non-Welfarist Perspective

– Aggregation Rules

•Collective Choice

•Distributive Justice

•A Class of Social Evaluation Functions

– Causal Inference

•Concept

•Modeling Implications

•Targeted Interventions

•Economy-Wide Policies

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The Living Standard

•A Multidimensional Concept– An outcome of interaction between opportunities

offered by society and readiness and ability of individual to identify and exploit such opportunities.

• Impossible to consider individual achievements in isolation from the natural and social environment.

– Identification of valuable dimensions depends on underlying view about personal features and social arrangements that are deemed important in the realization of any freely chosen life plan.

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The Living Standard

•Welfarist Approach– Indicators of the living standard based solely on

individual preferences or utility. [Welfare understood as the satisfaction of preferences (Hausman and McPherson, 1996)]

•Preferences are unobservable, hence must be revealed by proxy indicators.

– Assumption: consumers purchase the best bundle of goods they can afford.

• Implication: level of expenditure on goods and services is a good proxy measure of the living standard.

– Limitations: approach ignores non-market goods and non-material human conditions not captured by consumption behavior.

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The Living Standard

•Non-Welfarist Approach– Pays more attention to such things as primary goods

(Rawls 1971) or empowerment/capabilities (World Bank 2001 and 2005, Sen 1999).

– Primary goods:

•Basic liberties

•Freedom of movement and choice of occupation

•Powers and prerogatives of offices and positions of responsibility

• Income and wealth

•The social bases of self respect

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The Living Standard•Non-Welfarist Approach

– Empowerment/capability perspective

•Opulence not equivalent to standard of living

•Important distinction between achievements and ability to achieve [outcomes from opportunities; functionings from capabilities]

–Achievements (or functionings):a set of activities and states (“doings” and “beings”) that constitute an individual’s life.

–Capabilities define the freedom of choice or the opportunity set.

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The Living Standard

•Non-Welfarist/Empowerment (continued)

– Emphasis on individual agency

•Internal capabilities versus combined capabilities (Nussbaum 2000)

– Basic capabilities correspond to one’s endowment at birth

– They mature into internal capabilities at the end of the formative phase (of life).

– Combined capabilities entail appropriately developed internal faculties supported by a favorable external environment for their fulfillment.

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The Living Standard

•The Millennium Development Goals (MDGs) are consistent with the empowerment (or capability) approach to the living standard

– Eradicate poverty and hunger

– Achieve universal primary education

– Promote gender equity

– Reduce child mortality

– Improve maternal health

– Combat major diseases

– Ensure environmental sustainability

– Develop a global partnership for development

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Aggregation Rules

•An aggregation rule establishes a relationship between individual and social aspects for the purpose of deciding an issue or evaluating alternatives.

– Aspects: interests, preferences, values, views, judgments, capabilities, resource endowments, etc…

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Aggregation Rules

•A collection of value judgments (or normative principles) defines a set of acceptable rules (or rules of the game).

– Sources: (1) Collective Choice Theory; (2) Principles of Distributive Justice

• Arrow’s Social Choice Framework

– A template for designing social welfare functions i.e. mechanisms for ranking social states.

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Aggregation Rules

•Arrow’s Framework (continued)

– Aggregation Mechanism

•Pareto: If everybody prefers a to b, then a is socially better than b.

•Non-dictatorship: the social decision should not depend on the preferences of a single individual, regardless of those of everybody else.

• Independence of irrelevant alternatives: social ranking of a vis-à-vis b should depend only on individual rankings of a and b, and nothing else.

•Universal domain: Whatever individual preferences may be, the social welfare function should always be able to rank alternatives. [Aggregation scheme must work for all possible preference profiles]

•Collective rationality: social ranking must be complete and transitive.

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Aggregation Rules

•Arrow’s Framework (continued)

– Outcome: There is no such social welfare function!

– Interpretations

•Decisional perspective

– There is no social-decision making mechanism that respects both rationality and citizens’ sovereignty.

– Other words: Impossible to have the choices of the people made by the people and for the people (Sen 1998)

•Evaluative implications

– Ordinal welfarism not suitable for distributional impact analysis: it excludes welfare comparisons both within and across states of the world.

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Aggregation Rules

•Distributive Justice– Assume cardinal welfarism with

interpersonal comparability

•Welfare is objectively measurable and comparable across individuals (e.g. life expectancy or income)

– Every society has rules governing the allocation of resources [benefits and burdens] among its members.

– Allocation: a collective decision about who gets a good or bears a burden (Young 1994).

•Such decisions are based on relevant characteristics of the claimants

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Aggregation Rules

•Distributive Justice– Horizontal equity: equal treatment of

equals

– All claimants who are identical in terms of relevant characteristics for the allocation problem at hand must be treated equally (i.e. get same share of whatever is being distributed).

– Unequals must be treated in proportion to relevant differences.

– Relevance of characteristics of claimants depends on chosen principle among the following (Moulin 2003)

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Aggregation Rules

•Distributive Justice– Exogenous rights: Claims to the resources

are set independently of the use of such resources and the responsibility in their production.

•Example: Allocation of organs for transplant based on strict equality of chances (lottery) or according to social status or wealth.

– Compensation: give extra resources to people who find themselves in unfortunate circumstances for which they cannot be held (morally) responsible.•Priority to those who can survive the shortest

time (or whose life would be most difficult) without a new organ.

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Aggregation Rules

•Distributive Justice

– Reward: Distribution of resources based on individual behavior (e.g. productive contribution).

•Priority to the patient who has waited the longest (first come first served)

– Fitness: Resources must go to the person who can make the best use of them.

•Priority to those with highest likelihood of survival (maximize chance of success of transplant)

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Aggregation Rules

•A Class of Social Evaluation Functions– Characterized in terms of real-valued

functions (social welfare functions) defined over the set of utility profiles and representing social welfare orderings.

•Completeness and transitivity of associated orderings

•Monotonicity: an increase in one agent’s welfare, ceteris paribus, increases social welfare (compatibility with Pareto optimality or efficiency-fitness, most basic concept in welfarism).

•Anonymity (Symmetry): do not pay attention to the identity of the agents but only to their level of welfare (utility). A manifestation of equal treatment of equals in the sense that agents cannot be discriminated on the basis of any other characteristics, but their utility levels.

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Aggregation Rules

•A Class of Social Evaluation Functions

– Focus (Independence of Unconcerned Individuals): Social evaluation should pay no attention to individuals with no vested interest in the outcome of the comparison.

– Additive property: Given a utility profile u, the social welfare function W(u) is additive if there is an increasing real-valued function g(.) such that

uuguW

n

ii

,)()(1

2222

Aggregation Rules

•A Class of Social Evaluation Functions– [A continuous ordering that respects the

focus assumption can be represented by an additive social welfare function]

– Pigou-Dalton Transfer Principle:•An expression of aversion for inequality. Given

two individuals, a transfer of resources from the better off to the less well-off increases social welfare.

•Can be implemented within the additive framework by making the g function concave.

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Aggregation Rules

•A Class of Social Evaluation Functions

– Independence of common scale

• to focus on positive levels of welfare (utility), particularly when individual welfare is measured on a ratio-scale (e.g. life expectancy) and therefore invariant to positive linear transformation.

•Hence rescaling all welfare levels in two social states would not change the underlying ranking (the order of magnitude of the utility level under comparison is irrelevant).

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Aggregation Rules

•A Class of Social Evaluation Functions

– Let W(u) be a continuous social welfare function satisfying at once: (1) independence of unconcerned individuals, (2) independence of common scale, and (3) Pigou-Dalton transfer principle. Then the function g(.) can be only one of the following 3 types (Moulin 2003):

(1) 10,)( puug pii

(2) )log()( ii uug

(3) quug qii 0,)( .

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Aggregation Rules

•A Class of Social Evaluation Functions– When p=1, we have classical utilitarian

social welfare function (consistent with sum-fitness: distribute resources so as to maximize total welfare of the claimants).

– As q tends to infinity, egalitarianism prevails (compensation principle).

– As p or q tends to zero (1) or (3) tends to (2): Nash social welfare function (usually expressed in multiplicative form).

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Causal Inference

•Concept

• Effect of a cause can be understood only in relation to another cause (Holland 1986).

– Akin to the idea of netting out the opportunity cost of a resource (what it would have earned in the next best alternative use) to estimate the benefit of its engagement in one activity.

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Causal Inference

•Modeling Implications

– To evaluate policy in terms of its consequences (individual and social welfare), one needs a model that predicts the total effect of policy implementation on individuals and society.

•Model links policy instruments to fundamental determinants of outcomes:

– Individual behavior

–Endowments (attributes related to will, ability, ownership of assets, affiliation)

–Rules of social interaction.

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Causal Inference

•Modeling Implications

– A comparison of the social state “with” the policy and the state “without” it, ceteris paribus, provides an estimate of the policy effect.

– Note the ceteris paribus clause: individual characteristics (observable or not) and other macro-events unrelated to policy implementation are confounding factors that must be controlled in order to get an unbiased estimate of policy impact.

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Causal Inference

•Targeted Interventions

– Potential Outcome

– Function of participation and characteristics (Smith and Todd 2005)

– Random coefficient model: impact of “treatment” or intervention varies across individual even conditional on xi.

iiiii ydydy 01 )1(

iiiiiiii uduuxxxy 001010 )]()()([)(

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Causal Inference

• Targeted Interventions

– Common effect model

•Unobservable characteristics are the same in exposure and non-exposure states.

•The function (xi)=[1(xi)-0(xi)] is constant with respect to observable characteristics.

•Note linearity of (xi) and state-invariance of unobservable term (no 0 or 1 subscript on ui).

iiii udxy

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Causal Inference

•Targeted Interventions

– Impact estimation depends on stochastic structure

•Exogenous Switching

– Orthogonality condition: random disturbance uncorrelated with observable characteristics (xi) and participation status (di), then case of

– OLS or Matching provide a consistent estimate of average impact on the treated

•Endogenous Switching

– Orthogonality breaks down due to the endogeneity of participation decision.

– Hence find a way to break the correlation between participation and outcomes and apply suitable estimation methods e.g. IV (instrumental variable) or Heckman.

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Causal Inference

•Economy-Wide Policies

– Scope of intervention may be so large that the whole population is affected (e.g. structural adjustment program).

– Hence difficult to select a valid control or comparison group.

– Need an economy-wide model such as a computable general equilibrium (CGE) to simulate the state with the policy and the counterfactual, and compare the corresponding distributions of welfare.

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Causal Inference

•Economy-Wide Policies

– A general equilibrium model is a logical representation of a socioeconomic system wherein the behavior of all participants is compatible.

– Each agent attempts to implement the best feasible option in pursuit of her objective

•Optimization framework: (1) actions a socioeconomic unit can take; (2) set of constraints; (3) objective function used to evaluate action.

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Causal Inference

•Economy-Wide Policies

– Market interaction based on quid pro quo (Lindblom 2001): each person’s claims to available goods and services limited by amount of income obtainable by that person’s successful sale of something of value on the market.

– Impact of shocks and policy interpreted in terms of individual behavioral and market adjustments induced by such events.

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Conclusion

• Analysis of the social impact of a policy requires a reliable social policy model.

• A policy model has two basic components

– Positive component to predict impact of policy on individual behavior subject to prevailing social interaction.

– Normative component (social evaluation function) to assess desirability of outcomes.

• Attribution of consequences to policy entails a normalized comparison of social states (e.g. policy versus counterfactual).

• In the end social evaluation is a matter of value judgments.

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References

• Hausman, Daniel M. and McPherson, Michael S. 1996. Economic Analysis and Moral Philosophy. Cambridge: Cambridge University Press.

• Holland, Paul W. 1986. Statistics and Causal Inference. Journal of the American Statistical Association, Vol. 81, No. 396: 945-960.

• Lindblom, C. E. 2001. The Market System: What Is It, How It Works and What to Make of It. New Haven, CT: Yale University Press.

• Moulin, Hervé J. 2003. Fair Division and Collective Welfare. Cambridge (Massachusetts): The MIT Press

• Nussbaum, Martha C. 2000. Women and Human Development: The Capabilities Approach Cambridge: Cambridge University Press.

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References• Rawls, John. 1971. A Theory of Justice. Cambridge

(Massachusetts): Harvard University Press

• Sen, A. 1999. Development as Freedom. New York: Alfred A. Knopf.

• Sen, A. 1998. The Possibility of Social Choice. Nobel Prize Lecture.

• Sen, A., Muellbauer, J., Kanbur, R.,Williams, B. 1987. The Living Standard. Cambridge: Cambridge University Press.

• Smith, Jeffrey A. and Todd, Petra E. 2005. Does Matching Overcome LaLonde’s Critique of Nonexperimental Estimators? Journal of Econometrics, Volume 125, No. 1-2: 305-353.

• World Bank. 2001. World Development Report 2000/2001: Attacking Poverty. Oxford: Oxford University Press.

• _________. 2006. World Development Report: Equity and Development. Oxford: Oxford University Press.

• Young, H. P. 1994. Equity: In Theory and Practice. Princeton, NJ: Princeton University Press.

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The End.