What is the Causal Effect of Information and Learning about a Public Good on Willingness to Pay?

In this study we elicit agents’ prior information set regarding a public good, exogenously give information treatments to survey respondents and subsequently elicit willingness to pay for the good and posterior information sets. The design of this field experiment allows us to perform theoretically motivated hypothesis testing between different updating rules: non-informative updating, Bayesian updating, and incomplete updating. We find causal evidence that agents imperfectly update their information sets. We also field causal evidence that the amount of additional information provided to subjects relative to their pre-existing information levels can affect stated WTP in ways consistent overload from too much learning. This result raises important (though familiar) issues for the use of stated preference methods in policy analysis.

Infrastructure Finance and Industrial Takeoff in England

That financial matters did not constrain industrial takeoff in the UK is generally accepted in the historical literature; in contrast, contemporary empirical analyses have found evidence that financial development can be a causal determinant of economic growth. We look to reconcile these findings by concentrating on a particular aspect of industrialising UK where inefficiencies in finance could have had bite: The finance of physical infrastructures. We document the historical record and develop the importance of spatial disaggregation and spillovers in both technological and financial development. We develop a simple model that captures the nature of infrastructure finance within a theory of endogenous growth where financial costs are endogenous. We argue that the conception of the finance-growth nexus as a largely static, aggregative phenomenon misses out a good deal of complexity and we relate that complexity to a number of implications for regulation of both financial systems and the emergence of infrastructures

Inflation Uncertainty, Exchange Rate Depreciation and Volatility: Evidence from Ghana, Mozambique and Tanzania

While flexible exchange rates facilitate stabilisation, exchange rate fluctuations can cause real volatility. This gives policy importance to the causal relationship between exchange rate depreciation and its volatility. An exchange rate may be expected to become more volatile when the underlying currency loses value. We conjecture that a reverse causation, which further weakens the currency, may be mitigated by price stability. Data from Ghana, Mozambique and Tanzania support this: depreciation makes exchange rate more volatile for all but volatility does not causes depreciation in Tanzania which has enjoyed a more stable inflation despite all countries adopting similar macro-policies since early 1990s.

Where is the economics in spatial econometrics?

Spatial econometrics has been criticized by some economists because some model specifications have been driven by data-analytic considerations rather than having a firm foundation in economic theory. In particular this applies to the so-called W matrix, which is integral to the structure of endogenous and exogenous spatial lags, and to spatial error processes, and which are almost the sine qua non of spatial econometrics. Moreover it has been suggested that the significance of a spatially lagged dependent variable involving W may be misleading, since it may be simply picking up the effects of omitted spatially dependent variables, incorrectly suggesting the existence of a spillover mechanism. In this paper we review the theoretical and empirical rationale for network dependence and spatial externalities as embodied in spatially lagged variables, arguing that failing to acknowledge their presence at least leads to biased inference, can be a cause of inconsistent estimation, and leads to an incorrect understanding of true causal processes.

Chasing Graduate Jobs?

This paper examines empirically the relationship between under-employment and migration amongst five cohorts of graduates of Scottish higher education institutions with micro-data collected by the Higher Education Statistical Agency. The data indicate that there is a strong positive relationship between migration and graduate employment—those graduates who move after graduation from Scotland to the rest of the UK or abroad have a much higher rate of graduate employment. Versions of probit regression are used to estimate migration and graduate employment equations in order to explore the nature of this relationship further. These equations confirm that there is a strong positive relationship between the probability of migrating and the probability of being in graduate employment even after other factors are controlled for. Instrumental variables estimation is used to examine the causal nature of the relationship by attempting to deal with the potential endogeneity of migration decisions. Overall the analysis is consistent with the hypotheses that a sizeable fraction of higher education graduates are leaving Scotland for employment reasons. In turn this finding suggests the over-education/under-employment nexus is a serious problem in Scotland.

Sharp Bounds on Heterogeneous Individual Treatment Responses

This paper discusses how to identify individual-specific causal effects of an ordered discrete endogenous variable. The counterfactual heterogeneous causal information is recovered by identifying the partial differences of a structural relation. The proposed refutable nonparametric local restrictions exploit the fact that the pattern of endogeneity may vary across the level of the unobserved variable. The restrictions adopted in this paper impose a sense of order to an unordered binary endogeneous variable. This allows for a uni.ed structural approach to studying various treatment effects when self-selection on unobservables is present. The usefulness of the identi.cation results is illustrated using the data on the Vietnam-era veterans. The empirical findings reveal that when other observable characteristics are identical, military service had positive impacts for individuals with low (unobservable) earnings potential, while it had negative impacts for those with high earnings potential. This heterogeneity would not be detected by average effects which would underestimate the actual effects because different signs would be cancelled out. This partial identification result can be used to test homogeneity in response. When homogeneity is rejected, many parameters based on averages may deliver misleading information.

Nominal Stability and Financial Globalization

Over the past four decades, advanced economies experienced a large growth in gross external portfolio positions. This phenomenon has been described as Financial Globalization. Over roughly the same time frame, most of these countries also saw a substantial fall in the level and variability of inflation. Many economists have conjectured that financial globalization contributed to the improved performance in the level and predictability of inflation. In this paper, we explore the causal link running in the opposite direction. We show that a monetary policy rule which reduces inflation variability leads to an increase in the size of gross external positions, both in equity and bond portfolios. This appears to be a robust prediction of open economy macro models with endogenous portfolio choice. It holds across different modeling specifications and parameterizations. We also present preliminary empirical evidence which shows a negative relationship between inflation volatility and the size of gross external positions.

Coordination in Public Good Provision: How Individual Volunteering is Impacted by the Volunteering of Others

In this analysis, we examine the relationship between an individual's decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one's private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighborhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.

Effects of Experience, Knowledge and Signals on Willingness to Pay for a Public Good

This paper compares how increases in experience versus increases in knowledge about a public good affect willingness to pay (WTP) for its provision. This is challenging because while consumers are often certain about their previous experiences with a good, they may be uncertain about the accuracy of their knowledge. We therefore design and conduct a field experiment in which treated subjects receive a precise and objective signal regarding their knowledge about a public good before estimating their WTP for it. Using data for two different public goods, we show qualitative equivalence of the effect of knowledge and experience on valuation for a public good. Surprisingly, though, we find that the causal effect of objective signals about the accuracy of a subject’s knowledge for a public good can dramatically affect their valuation for it: treatment causes an increase of $150-$200 in WTP for well-informed individuals. We find no such effect for less informed subjects. Our results imply that WTP estimates for public goods are not only a function of true information states of the respondents but beliefs about those information states.

Coordination in Public Good Provision: How Individual Volunteering is Impacted by the Volunteering of Others

In this analysis, we examine the relationship between an individual’s decision to volunteer and the average level of volunteering in the community where the individual resides. Our theoretical model is based on a coordination game , in which volunteering by others is informative regarding the benefit from volunteering. We demonstrate that the interaction between this information and one’s private information makes it more likely that he or she will volunteer, given a higher level of contributions by his or her peers. We complement this theoretical work with an empirical analysis using Census 2000 Summary File 3 and Current Population Survey (CPS) 2004-2007 September supplement file data. We control for various individual and community characteristics, and employ robustness checks to verify the results of the baseline analysis. We additionally use an innovative instrumental variables strategy to account for reflection bias and endogeneity caused by selective sorting by individuals into neighbourhoods, which allows us to argue for a causal interpretation. The empirical results in the baseline, as well as all robustness analyses, verify the main result of our theoretical model, and we employ a more general structure to further strengthen our results.

Can Early Intervention Policies Improve Well-being? Evidence from a randomized controlled trial

Many authors have proposed incorporating measures of well-being into evaluations of public policy. Yet few evaluations use experimental design or examine multiple aspects of well-being, thus the causal impact of public policies on well-being is largely unknown. In this paper we examine the effect of an intensive early intervention program on maternal well-being in a targeted disadvantaged community. Using a randomized controlled trial design we estimate and compare treatment effects on global well-being using measures of life satisfaction, experienced well-being using both the Day Reconstruction Method (DRM) and a measure of mood yesterday, and also a standardized measure of parenting stress. The intervention has no significant impact on negative measures of well-being, such as experienced negative affect as measured by the DRM and global measures of well-being such as life satisfaction or a global measure of parenting stress. Significant treatment effects are observed on experienced measures of positive affect using the DRM, and a measure of mood yesterday. The DRM treatment effects are primarily concentrated during times spent without the target child which may reflect the increased effort and burden associated with additional parental investment. Our findings suggest that a maternal-focused intervention may produce meaningful improvements in experienced well-being. Incorporating measures of experienced affect may thus alter cost-benefit calculations for public policies.