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Administration of pediatric anesthetics with N-methyl D-aspartate (NMDA)-receptor antagonist and/or γ-aminobutyric acid (GABA) agonist activities may result in neuronal degeneration and/or neuronal cell death in neonatal rats. Evaluating pediatric drug candidates for this potential neurotoxicity is often part of overall preclinical new drug development strategy. This specialized assessment may require dosing neonatal rats at postnatal day 7 at the peak of the brain growth spurt and evaluating brain tissue 24 to 48 hours following dosing. The need to identify methods to aid in the accurate and reproducible detection of lesions associated with this type of neurotoxic profile is paramount for meeting the changing needs of neuropathology assessment and addressing emerging challenges in the neuroscience field. We document the use of Fluoro-Jade B (FJB) staining, to be used in conjunction with standard hematoxylin and eosin staining, to detect acute neurodegeneration and neuronal cell death that can be caused by some NMDA-receptor antagonists and/or GABA agonists in the neonatal rat brain. The FJB staining is simple, specific, and sensitive and can be performed on brain specimens from the same cohort of animals utilized for standard neurotoxicity assessment, thus satisfying animal welfare recommendations with no effect on achievement of scientific and regulatory goals.

Quality-adjusted population density (QAPD) is population divided by land area that has been adjusted for geographic characteristics. We derive weights on these geographic characteristics from a global regression of population density at the quarter-degree level with country fixed effects. We show, first, that while income per capita is uncorrelated with conventionally measured population density across countries, there is a strong negative correlation between income per capita and QAPD; second, that the magnitude of this relationship exceeds the plausible structural effect of density on income, suggesting a negative correlation between QAPD and productivity or factor accumulation; and third, that higher QAPD in poor countries is primarily due to population growth since 1820. We argue that these facts are best understood as results of the differential timings of economic takeoff and demographic transition across countries, and particularly the rapid transfer of health technologies from early to late developers.

Does a person's historical lineage influence his or her current economic status? Motivated by a large literature in the social sciences stressing the effect of an early transition to agriculture on current economic performance at the country level, we examine the relative contemporary status of individuals as a function of how much their ancestors relied on agriculture during the preindustrial era. We focus on Africa, where—by combining anthropological records of groups with individual-level survey data—we can explore the effect of the historical lifeways of one's forefathers. Within enumeration areas (typically a single village or group of villages in the countryside and a city block in urban areas) as well as occupational groups, we find that individuals from ethnicities that derived a larger share of subsistence from agriculture in the precolonial era are today more educated and wealthy. A tentative exploration of channels suggests that differences in attitudes and beliefs as well as differential treatment by others, including differential political power, may contribute to these divergent outcomes.

Iodine deficiency is the leading cause of preventable mental retardation in the world today. The condition, which was common in the developed world until the introduction of iodized salt in the 1920s, is connected to low iodine levels in the soil and water. We examine the impact of salt iodization on cognitive outcomes in the United States by taking advantage of this natural geographic variation. Salt was iodized over a short period of time beginning in 1924. We use military data collected during World War I and World War II to compare outcomes of cohorts born before and after iodization in localities that were naturally poor and rich in iodine. We find that for the one-quarter of the population most deficient in iodine this intervention raised intelligence quotient (IQ) by approximately one standard deviation. Our results can explain roughly one decade’s worth of the upward trend in IQ in the United States (the Flynn effect). We also document a large increase in thyroid-related deaths following the countrywide adoption of iodized salt, which affected mostly older individuals in localities with high prevalence of iodine deficiency.

Abstra c t As populations age, the degree to which workers׳ human capital reflects the cutting edge of technology falls because education took place further in the past. This “pure vintage” effect of aging is well known. In this paper, we explore a second effect of aging: in an older population, older teachers pass on knowledge that was current further in the past. We show that this “teacher multiplier” can significantly increase the technological backwardness of the labor force. We present both an analytic model that can be solved for steady states and a numerical model that can describe transitions in the average vintage of human capital as population age structure changes over time. We also discuss evidence on the effect of age on the technological up-to-dateness of workers in general and teachers in particular.

This book explores the relationship between the material standard of living and health, both across countries and over time. Above all, Deaton is interested in the question of whether income growth contributes significantly to better health. His answer is no: saving lives in poor countries is not expensive, and there are many episodes of massive health improvements in the absence of income growth. As an alternative, he argues that the cross-sectional correlation between health and income is induced by variation in institutional quality, while over time, parallel improvements in income and health have been a result of advancing knowledge. (JEL E23, I12, I14, I15, O15, O47)

In Capital in the Twenty-First Century, Thomas Piketty uses the market value of tradable assets to measure both productive capital and wealth. As a measure of wealth this is problematic because it ignores the value of human capital and transfer wealth, which have grown enormously over the last 300 years. Thus the constancy of the wealth/income ratio as portrayed in his data is an illusion. Further, the types of wealth that he does not measure are more equally distributed than tradable assets. The approach also incorrectly identifies capital gains due to reduced discount rates as increases in the capital stock.

I examine recent changes in African mortality and discuss their potential economic and demographic effects. Growth in life expectancy sharply departed from its trend after 1990, and then experienced a sharp acceleration after 2005. This latter acceleration was due overwhelmingly to improvements in HIV and malaria. Economists differ in their estimates of how large the structural effect of health on income is, with many estimates being relatively small. Taking seriously the delays built into many plausible causal channels would lead one to expect that any economic effects of these mortality changes, if they are detectable at all, will not appear for several decades. By contrast, the effect of declining mortality, especially from malaria, should soon be visible in data on population age structure in some countries.

Older Americans have experienced dramatic gains in life expectancy in recent decades, but an emerging literature reveals that these gains are accumulating mostly to those at the top of the income distribution. We explore how growing inequality in life expectancy affects lifetime benefits from Social Security, Medicare, and other programs and how this phenomenon interacts with possible program reforms. We first project that life expectancy at age 50 for males in the two highest income quintiles will rise by 7 to 8 years between the 1930 and 1960 birth cohorts, but that the two lowest income quintiles will experience little to no increase over that time period. This divergence in life expectancy will cause the gap between average lifetime program benefits received by men in the highest and lowest quintiles to widen by $130,000 (in $2009) over this period. Finally we simulate the effect of Social Security reforms such as raising the normal retirement age and changing the benefit formula to see whether they mitigate or enhance the reduced progressivity resulting from the widening gap in life expectancy.

M-Pesa, a service operated by the mobile phone network Safaricom in Kenya, allows users to deposit money onto their telephone handsets, transfer e-money to another user with a simple text message, and withdraw cash at one of thousands of outlets throughout the country. The system is safer, cheaper, and far faster than the money transfer systems that it replaced. Although only five years old, M-Pesa has achieved remarkable penetration into the Kenyan economy. As of September, 2011, there were 32,000 M-Pesa outlets at which individuals could exchange cash for e-float or vice-versa, in a country that as of 2009 had 491 bank branches, 500 postbank branches, and 352 ATMs (Mas and Ng’weno, 2009). In the six month period April-September, 2011, the volume of transfers was Ksh. 314 billion, compared to nominal GDP of Ksh. 2.99 trillion that year. (For the period from which our data are drawn, the market exchange rate was approximately 75 Ksh/dollar and the PPP exchange rate was approximately 35 Ksh./dollar). At present, M-Pesa is primarily a money transfer system. However, it has the potential to evolve in two exciting directions: first as a gateway via which unbanked households can access financial services, and second, as a transaction medium, with e-money partially replacing cash.1 Even in its current form, however, M-Pesa represents a dramatic change in the economic environment of Kenyan households. Further, data on how households use M-Pesa allows for insight into the objectives of and constraints on their money management choices, and consumption more generally.

Does a person's historical lineage influence his or her current economic status? Motivated by a large literature in social sciences stressing the effect of an early transition to agriculture on current economic performance at the level of countries, we examine the relative contemporary status of individuals as a function of how much their ancestors relied on agriculture during the pre-industrial era. We focus on Africa, where by combining anthropological records of groups with individual level survey data we can explore the effect of the historical lifeways of one's forefathers. Within enumeration areas and occupational groups, we find that individuals from ethnicities that derived a larger share of subsistence from agriculture in the precolonial era are today more educated and wealthy. A tentative exploration of channels suggests that differences in attitudes and beliefs as well as differential treatment by others, including differential political power, may contribute to these divergent outcomes.

We examine the effects of population aging due to declining fertility and rising elderly life expectancy on consumption possibilities in the presence of intergenerational transfers. Our analysis is based on a highly tractable continuous-time overlapping generations model in which the population is divided into three groups (youth dependents, workers, and elderly dependents) and lifecourse transitions take place in a probabilistic fashion. We show that the consumption-maximizing response to greater longevity in highly developed countries is an increase in fertility. However, with larger transfer payments, the actual fertility response will likely be the opposite, leading to further population aging.

Most readers of this article are already familiar with images of the “Earth at Night,” which are really montages showing satellite views of visible lights.1 Looking at such images, it is easy to see that the brightness of visible lights is strongly related to both population density and income per capita. The effect of population density shows up in the visibility of urban agglomerations, coastlines, river valleys, and even the higher density of population along the paths of highways and railroads. Similarly, the Northeastern United States is far brighter than the mountain West, even though they have similarly levels of income. The effect of income is similarly easy to see. Sharp economic boundaries, such as the inter-Korean border show up plainly. India, with a population density slightly higher than Japan, is significantly dimmer, The observation that income per capita is one of the determinants of visible light suggests that one might potentially use visible light to help measure income. In this paper, we explore the usefulness of these night lights data to economists studying issues related to economic growth and the national or local level. In particular, we ask the extent to which lights data can augment or entirely replace data on Gross Domestic Product.2 There are a number of obstacles to using lights visible from space to measure income, broadly falling into two categories. First, the relationship between economic activity and the true amount of light emanating from the Earth’s surface is not constant across time and space. Light visible from space is a byproduct of consumption and production activities, but light is hardly produced in a fixed ratio to output. Some productive activities such as steelmaking produce a lot of light; others such as software design produce very little. Countries or regions may differ in the fraction of their economic activity that takes place after dark (for example, Las Vegas vs. Salt Lake City). Patterns of settlement (for example, whether people live in multi-storey buildings), the availability of hydropower, etc. may all affect how much light is visible from space for a given level of income and population. Second, true light is imperfectly measured by the satellites. Humidity, reflectivity, and time periods excluded from coverage because of sunlight, moonlight, and cloud cover contamination all differ across the globe. Sensor scale for recording lights in practice varies across satellites and as satellites age over time. If one is measuring economic growth, some of the location-specific factors are differenced out. The rest we treat as measurement error in the relationship between GDP growth and light growth. We note that while we focus on measuring total income growth of regions, one might be also interested in growth in income per capita. We don’t pursue that here although we have explored the issue by using population growth numbers to supplement lights growth. Population is both conceptually and practically easier to measure than is income, so it is also feasible to alternatively focus on income growth per capita. Despite problems, the night lights data have several advantages. The first has to do with the nature of measurement error in lights data. A number of studies have recently reminded economists that much of the data on GDP growth in developing countries is plagued by serious measurement error. For example, Johnson et al. (2009) study revisions in the Penn World Tables, a standard measure of GDP. They find that comparing version 6.1 of that data, released in 2002, with version 6.2 released in 2006, the standard deviation of the change in countries’ average growth over the period 1970–1999 was 1.1% per year (which is very large relative to the average growth rate of 1.56% per year). This indicates that at least one of the measures, and presumably both, contained a great deal of error. We do not claim that the measurement error in the night lights data is smaller than that in conventional data, but we do think that the two forms of measurement error are poorly or not correlated. It is well know that combing two problematic measures can produce a composite with smaller measurement error than either of them. A second advantage of the night lights data is that they are available for regions for which standard GDP measures are not. These include sub-national units such as cities and regions, as well as entities that cross national borders, like biomes. Economic analysis of growth and of the impacts of policies and events on cities and regions of many countries is hindered by a complete absence of any regular measure of local economic activity. Much of the interesting variation in economic growth takes place within rather than between countries. However, for the vast majority of economics research, “empirical analysis of growth” has become synonymous with use of national accounts data. The night lights data offer a tool that allows the researcher to set aside this limitation. The rest of this paper is organized as follows. In Section I, we briefly discuss the night lights data. Section II outlines our statistical approach to combining data from lights with conventional measures of GDP, and presents results of an exercise applying our technique to a set of low and middle income countries. Section III discusses an application beyond the measurement of national income. We refer the reader to our companion paper, Henderson, Storeygard, and Weil (2009), for more detailed discussion of many of the technical and statistical issues raised here.

In Capital in the 21st Century, Thomas Piketty uses the market value of tradeable assets to measure both productive capital and wealth. As a measure of wealth this is problematic because it ignores the value of human capital and transfer wealth, which have grown enormously over the last 300 years. Thus the constancy of the wealth/income ratio as portrayed in his data is an illusion. Further, the types of wealth that he does not measure are more equally distributed than tradeable assets. The approach also incorrectly identifies capital gains due to reduced discount rates as increases in the capital stock.

In Capital in the 21st Century, Thomas Piketty uses the market value of tradeable assets to measure both productive capital and wealth. As a measure of wealth this is problematic because it ignores the value of human capital and transfer wealth, which have grown enormously over the last 300 years. Thus the constancy of the wealth/income ratio as portrayed in his data is an illusion. Further, the types of wealth that he does not measure are more equally distributed than tradeable assets. The approach also incorrectly identifies capital gains due to reduced discount rates as increases in the capital stock.Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Previous experiments have demonstrated that significant increases in yield of Agaricus bisporus mushrooms were achieved by adding a micronutrient rich fertilizer, Micromax, to the compost. This study was performed to determine the mineral(s) that are responsible for this yield improvement. An initial experiment determined that manganese was the mineral of primary importance; addition of 184 mg kg-1 Mn increased yield by 10.8%, compared to the control. Subsequent experiments demonstrated that the addition of manganese to the compost has a stimulatory effect on mushroom yields. Significant yield increases, ranging from 9.6% to 11.8% (compared to the control), were observed as a result of manganese additions varying between 50 and 300 mg kg-1. Also, data from the last set of experiments indicated that Micromax additions always resulted in greater yields indicating that micronutrients in Micromax, in addition to manganese, may be responsible for increasing yields.

Hydrolysis of the imine perfluoro-5-aza-4-nonene, C 3 F 7 CFNC 4 F 9 , in ether was studied by several spectroscopic techniques including 17 O NMR. The initial product is C 3 F 7 CONHC 4 F 9 which is converted to (C 3 F 7 CO) 2 NH and then to C 3 F 7 CONH 2 and C 3 F 7 CO 2 H. Solvolysis in liquid ammonia afforded the amidine C 3 F 7 C(NH)NH 2 . Reaction with hydrazine produced 3,5-bis(heptafluoropropyl)-1,2,4-triazole whose crystal structure is reported.

Treatment of the bis(perfluoroalkyl)triazapentadiene PhN=C(C(3)F(7))-N=C(C(3)F(7))-NHPh, 2, with bases affords salts of the conjugate base. Alkylation of the Na(+) salt with CH(3)I yields PhN=C(C(3)F(7))-N=C(C(3)F(7))-NMePh. The crystal structure of [Bu(4)N][Ph(2)N(3)C(2)(C(3)F(7))(2)] demonstrates a twisted, zigzag geometry for the anion in the solid state, but in solution, it is conformationally unstable. Both compounds are stable in aqueous methanol, but hydrolysis occurs under acidic conditions. Protonation with CF(3)SO(3)H acid occurs at the sp(2) nitrogen to give [PhN-(H) HC(C(3)F(7))-C(C(3)F(7))-NHPh][CF(3)SO(3)]. Heating 2 in CF(3)SO(3)H produces 2,4-bis(heptafluoropropyl)-1,3-quinazoline.

Results of the acid catalyzed oligomerization of 2‐alkenyl‐5(4H)‐oxazolones are reported. Employing LC–MS and preparative LC methods, the oligomeric mixtures were characterized by NMR analyses and were discovered to consist of exclusively cyclic trimers to decamers, with tetramers and pentamers predominating. A nucleophilic oligomerization mechanism involving Michael addition and C‐alkylation of a ketene‐aminal to protonated monomer was proposed that resulted in irreversible cyclization at the trimer propagation stage. Subsequent oligomerization proceeded via enolization of α‐hydrogens on 2‐substituted 5(4H)‐oxazolone products and continued Michael addition to protonated monomer. In the sense that when both enolizable hydrogens and protonated monomer are present, the oligomerization can be regarded as being “living.”

We construct a matrix showing the share of the year 2000 population in every country that is descended from people in different source countries in the year 1500. Using this matrix, we analyze how post-1500 migration has influenced the level of GDP per capita and within-country income inequality in the world today. Indicators of early development such as early state history and the timing of transition to agriculture have much better predictive power for current GDP when one looks at the ancestors of the people who currently live in a country than when one considers the history on that country’s territory, without adjusting for migration. Measures of the ethnic or linguistic heterogeneity of a country’s current population do not predict income inequality as well as measures of the ethnic or linguistic heterogeneity of the current population’s ancestors. An even better predictor of current inequality in a country is the variance of early development history of the country’s inhabitants, with ethnic groups originating in regions having longer histories of agriculture and organized states tending to be at the upper end of a country’s income distribution. However, high within-country variance of early development also predicts higher income per capita, holding constant the average level of early development.

This chapter examines the relationship between health and economic growth. Across countries, income per capita is highly correlated with health, as measured by life expectancy or a number of other indicators. Within countries, there is also a correlation between people’s health and income. Finally, over time, the historical evolution of cross-country health differences has largely paralleled the evolution of income differences, with the exception that in the last half century the convergence of health has been much faster than the convergence of income. How are health and income related? Theoretically, there is good reason to believe that causality runs in both directions. Healthier individuals are more productive, learn more in school, and, because they live longer, face enhanced incentives to accumulate human capital. Similarly, higher income for individuals or countries improves health in a variety of ways, ranging from better nutrition to construction of public health infrastructure. Empirically, there is evidence for both of these causal channels being operative, but the magnitude of the effects is limited, at least as they apply to cross-sectional differences among countries or individuals. Apparently, other factors that simultaneously raise income and improve health outcomes, such as institutional quality (for countries) and human capital (for individuals), are responsible for a good deal of the observed health–income correlation. The final section of the chapter discusses measures of aggregate welfare that combine consumption and life expectancy.

We examine the role of increased life expectancy in raising human capital investment during the process of economic growth. We develop a continuous time, overlapping generations model in which individuals make optimal schooling investment choices in the face of a constant probability of death. We present analytic results, followed by results from a calibrated version of the model using realistic estimates of the return to schooling. Mortality decline produces economically significant increases in schooling and consumption. Allowing schooling to vary endogenously produces a much larger response of consumption and capital to mortality decline than is observed when schooling is held fixed.

Saving and growth are strongly positively correlated across countries. Recent empirical evidence suggests that this correlation holds largely because high growth leads to high saving, not the other way around. This evidence is difficult to reconcile with standard growth models, since forward-looking consumers with standard utility should save less in a fast-growing economy because they know they will be richer in the future than they are today. We show that if utility depends partly on how consumption compares to a “habit stock” determined by past consumption, an otherwise-standard growth model can imply that increases in growth can cause increased saving. (JEL D91, E21, O40)

This paper develops a unified growth model that captures the historical evolution of population, technology, and output. It encompasses the endogenous transition between three regimes that have characterized economic development. The economy evolves from a Malthusian regime, where technological progress is slow and population growth prevents any sustained rise in income per capita, into a Post-Malthusian regime, where technological progress rises and population growth absorbs only part of output growth. Ultimately, a demographic transition reverses the positive relationship between income and population growth, and the economy enters a Modern Growth regime with reduced population growth and sustained income growth. (JEL J13, O11, O33, O40)

This paper examines how population growth affects the average level of utility particularly the consumption per capita. It also focuses on the effects of population growth on the ratio of dependent consumers to working-age adults. The model employed in this paper has three demographic groups: working-age adults who produce and consume and the young and elderly who only consume. This study concluded that the transition to lower population growth requires a long period of reduced dependency in which society benefits from lower spending on children while it has yet to pay for higher old-age dependency. The dependency level after 30 years is not significantly different from that which would exist in an optimal stable population. Any rise in fertility that would decrease old-age dependency in the long run would require a lengthy period of higher-than-steady-state dependency.

We examine the role of declining mortality in explaining the rise of retirement over the course of the twentieth century. We construct a model in which individuals make labor/leisure choices over their lifetimes subject to uncertainty about their dates of death. In an environment with high mortality, an individual who saves for retirement faces a high risk of dying before he can enjoy his planned leisure. In this case, the optimal plan is for people to work until they die. As mortality falls, however, it becomes optimal to plan, and save for, retirement. We analyze our model using two mathematical formulations of the survival function as well as data on actual changes in the US life table over the last century, and show that this “uncertainty effect” of declining mortality would have more than outweighed the “horizon effect” by which rising life expectancy would have led to later retirement.

I examine the economic effects of disease and disease control. I consider both the effect of disease on conventionally measured GDP and also the monetary equivalent of the utility benefits from lower mortality. Regarding the effects on conventional GDP, I evaluate a number of approaches including cross-country regression (with and without instruments for disease) and simulation based on microeconomic studies. I also discuss theoretically and empirically the different channels that link disease and economic outcomes, including effects that run through labour productivity, education and population growth. Different approaches yield somewhat different results, but the overall finding is that there is at best weak support for the claims that the disease burden in Africa significantly lowers GDP or that improving health would provide a big impetus to economic growth. In contrast, the monetary equivalent of the utility benefits from better health can be extremely large. For example, reduced mortality in many developing countries has made a contribution to utility of roughly the same value as the growth of conventional GDP over the last several decades. Copyright 2010 The author 2010. Published by Oxford University Press on behalf of the Centre for the Study of African Economies. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

We examine the effect of malaria on economic development in Africa over the very long run. Using data on the prevalence of the mutation that causes sickle cell disease we measure the impact of malaria on mortality in Africa prior to the period in which formal data were collected. Our estimate is that in the more afflicted regions, malaria lowered the probability of surviving to adulthood by about ten percentage points, which is roughly twice the current burden of the disease. The reduction in malaria mortality has been roughly equal to the reduction in other causes of mortality. We then ask whether the estimated burden of malaria had an effect on economic development in the period before European contact. Examining both mortality and morbidity, we do not find evidence that the impact of malaria would have been very significant. These model-based findings are corroborated by a more statistically-based approach, which shows little evidence of a negative relationship between malaria ecology and population density or other measures of development, using data measured at the level ethnic groups.

This paper examines a novel mechanism linking fertility and growth. Household fertility is determined by relative wages of women and men. Increasing women's wages reduces fertility by raising the cost of children relatively more than household income. Lower fertility raises the level of capital per worker which in turn, since capital is more complementary to women's labor input than men's, raises women's relative wages. This positive feedback leads to the possibility of multiple steady-state equilibria. Countries with low initial capital may converge to a development trap with high fertility, low capital, and low relative wages for women.

We take issue with Angelini's (1994) claim that the founding of the Federal Reserve was not responsible for a change in the stochastic process followed by short-term interest rates. We argue that Angelini's failure to reject the null hypothesis of no regime change around the date of the founding of the Fed is due to the low power of his test.

We examine the relationship between income growth and saving using both cross-country and household data. At the aggregate level, we find that growth Granger causes saving, but saving does not Granger cause growth. Using household data, we find that households with predictably higher income growth save more than households with predictably low growth. We argue that standard permanent income models of consumption cannot explain these findings, but a model of consumption with habit formation may. The positive effect of growth on saving implies that previous estimates of the effect of saving on growth may be overstated.

Examination of household (micro) data on the elderly has generally concluded that they do not dissave significantly, whereas estimates using aggregate (macro) data have shown that the presence of a large elderly population leads to a lower saving rate. This paper shows that if interactions between generations are important, one would not expect these estimates to be the same. The paper presents new evidence that bequests are plausibly the source of this discrepancy. Examination of data from young households that have received or expect bequests confirms that bequests are indeed an important factor determining the saving of the young.

We assess quantitatively the effect of exogenous reductions in fertility on output per capita. Our simulation model allows for effects that run through schooling, the size and age structure of the population, capital accumulation, parental time input into child-rearing, and crowding of fixed natural resources. The model is parameterized using a combination of microeconomic estimates, data on demographics and natural resource income in developing countries, and standard components of quantitative macroeconomic theory. We apply the model to examine the effect of a change in fertility from the UN medium-variant to the UN low-variant projection, using Nigerian vital rates as a baseline. For a base case set of parameters, we find that such a change would raise output per capita by 5.6 percent at a horizon of 20 years, and by 11.9 percent at a horizon of 50 years.

We assess quantitatively the effect of exogenous reductions in fertility on output per capita. Our simulation model allows for effects that run through schooling, the size and age structure of the population, capital accumulation, parental time input into child-rearing, and crowding of fixed natural resources. The model is parameterized using a combination of microeconomic estimates, data on demographics and natural resource income in developing countries, and standard components of quantitative macroeconomic theory. We apply the model to examine the effect of a change in fertility from the UN medium-variant to the UN low-variant projection, using Nigerian vital rates as a baseline. For a base case set of parameters, we find that such a change would raise output per capita by 5.6 percent at a horizon of 20 years, and by 11.9 percent at a horizon of 50 years.

M-Pesa is a mobile phone based money transfer system in Kenya which grew at a blistering pace following its inception in 2007. We examine how M-Pesa is used as well as its economic impacts. Analyzing data from two waves of individual data on financial access in Kenya, we find that increased use of M-Pesa lowers the propensity of people to use informal savings mechanisms such as ROSCAS, but raises the probability of their being banked. Using aggregate data, we calculate the velocity of M-Pesa at roughly four person-to-person transfers per month. In addition, we find that M-Pesa causes decreases in the prices of competing money transfer services such as Western Union. While we find little evidence that people use their M-Pesa accounts as a place to store wealth, our results suggest that M-Pesa improves individual outcomes by promoting banking and increasing transfers.

We assess quantitatively the effect of exogenous reductions in fertility on output per capita. Our simulation model allows for effects that run through schooling, the size and age structure of the population, capital accumulation, parental time input into child-rearing, and crowding of fixed natural resources. The model is parameterized using a combination of microeconomic estimates, data on demographics and natural resource income in developing countries, and standard components of quantitative macroeconomic theory. We apply the model to examine the effect of an intervention that immediately reduces TFR by 1.0, using current Nigerian vital rates as a baseline. For a base case set of parameters, we find that an immediate decline in the TFR of 1.0 will raise output per capita by approximately 13.2 percent at a horizon of 20 years, and by 25.4 percent at a horizon of 50 years.

M-Pesa is a mobile phone based money transfer system in Kenya which grew at a blistering pace following its inception in 2007. We examine how M-Pesa is used as well as its economic impacts. Analyzing data from two waves of individual data on financial access in Kenya, we find that increased use of M-Pesa lowers the propensity of people to use informal savings mechanisms such as ROSCAS, but raises the probability of their being banked. Using aggregate data, we calculate the velocity of M-Pesa at roughly four person-to-person transfers per month. In addition, we find that M-Pesa causes decreases in the prices of competing money transfer services such as Western Union. While we find little evidence that people use their M-Pesa accounts as a place to store wealth, our results suggest that M-Pesa improves individual outcomes by promoting banking and increasing transfers.