Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T17:24:57.346Z Has data issue: false hasContentIssue false

Identifying the Rich: Registration, Taxation, and Access to the State in Tanzania

Published online by Cambridge University Press:  19 May 2023

JEREMY BOWLES*
Affiliation:
Stanford University, United States
*
Jeremy Bowles, Postdoctoral Fellow, King Center on Global Development, Stanford University, United States, jbowles@stanford.edu.
Rights & Permissions [Opens in a new window]

Abstract

How do states build their informational capacity? This article argues that distributive politics conditions how the state’s capacity develops. I study civil registration, where citizens comply with the state’s informational demands in exchange for documentary proof of identity, which may simultaneously facilitate access to public resources and exposure to taxation. Though the rich are particularly threatened by taxation, the narrow benefits of registration induce their compliance over that of the poor. I leverage a set of reforms in early postindependence Tanzania which provide quasi-random variation in citizens’ registration status and show that registration promotes access to narrow-based resources, rather than broad-based ones, while increasing tax payment. In turn, citizens’ decisions to comply reflect the economically stratified local incidence of these net benefits. The results suggest how nominally universal state-building schemes can have regressive effects on the state’s coverage.

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the American Political Science Association

INTRODUCTION

Classic accounts of the state posit that its capacity is constituted by what it knows about its population (Foucault Reference Foucault1991; Giddens Reference Giddens1986; Mann Reference Mann1984; Scott Reference Scott1998). As Scott (Reference Scott1998) writes in his seminal analysis of legibility, “An illegible society is a hindrance to any effective intervention by the state, whether the purpose of that intervention is plunder or public welfare” (78). Recent studies, accordingly, have demonstrated important variation in this informational capacity, as measured through censuses, cadasters, and registries, and validated its independent effects on taxation and the delivery of public goods (Brambor et al. Reference Brambor, Goenaga, Lindvall and Teorell2020; Christensen and Garfias Reference Christensen and Garfias2021; D’Arcy and Nistotskaya Reference D’Arcy and Nistotskaya2017; Lee and Zhang Reference Lee and Zhang2017). Much less is known, however, about how such capacity is built: how do states obtain information from their citizens, and who are they able to learn about?

I argue that distributive politics conditions how the state’s capacity develops. When coercion is prohibitively expensive, the state must rely on the instrumental compliance of citizens with state-building schemes (Levi Reference Levi1988; Migdal Reference Migdal1988). Since the state’s informational capacity affects its ability to tax its citizens (Kiser and Sacks Reference Kiser, Sacks, Martin, Mehrotra and Prasad2009; Stasavage Reference Stasavage2020), building this capacity relies on structuring the parameters of informational transactions with citizens that induce them to comply in spite of the costs. In this article, I consider how these parameters are set, articulate their implications for the state’s coverage, and take advantage of a rich empirical setting in postindependence Tanzania to provide quasi-experimental evidence supporting the argument.

I focus on the case of identity registration schemes, perhaps the most ubiquitous mechanism through which states solicit information from their citizens. In complying with state demands for information, citizens trade off potential increases in both their access to public resources and their exposure to taxation. When bureaucratic capacity is moderate and democratic political competition is weak, state-building schemes to register citizens have especially economically stratified results. Moderate bureaucratic capacity renders the state selectively capable of regulating access to narrow-based public resources on the basis of registration status. Limited competition, by weakening redistributive pressures, dampens the concerns of higher economic status citizens about registering with the state. Together, the benefits of compliance become nonuniform even absent variation in citizens’ logistical and financial costs. Rendering this incidence self-enforcing, to the extent that the state fiscally benefits by taxing those citizens with more economic resources, it faces only weak incentives to induce the registration of relatively poorer citizens.

Such seemingly administrative state-building schemes then have particularly regressive implications: rather than universalizing access, registration technologies can undergird and entrench economic inequalities in state–citizen interaction. The first empirical prediction of the theoretical framework is that supplying information to the state through registration should facilitate access to narrow-based public resources of particular value to higher economic status citizens, in exchange for increased exposure to taxation. The second is that citizens’ decisions whether to register in the first place ought to be conditioned by the relative balance of these returns. Registration, however, is not randomly assigned and so any analysis of its effects must account for major confounders, such as rurality, income, and education, which also independently affect access to the state. Consequently, no credibly causally identified evidence appears to exist on its effects.

I study civil registration in Tanzania in the state-building period following independence in 1961, which offers an appropriate but challenging case.Footnote 1 The state’s moderate bureaucratic capacity rendered it selectively capable of regulating access to public resources but, in spite of limited political competition, the regime’s socialist orientation posed a strong redistributive threat to relatively wealthier citizens electing to supply information to the state. Descriptive evidence underscores the strong link between registration and taxation during this period (Due Reference Due1963; Lee Reference Lee1965), the extent to which citizens were aware of the trade-offs they faced in registering with the state (Harris Reference Harris1965; Hunter Reference Hunter2015; Kjekshus Reference Kjekshus1974), and how these were especially salient for wealthier citizens due to the progressive incidence of taxation (Huang Reference Huang1976).

To evaluate the theory’s empirical implications, I leverage a series of legal reforms—common across the region during this period—that sought to induce registration in a set of districts in the mid-1960s. Using rich historical and administrative data sources, in a difference-in-differences setup, I first compare individuals in cohorts born shortly after, versus before, the reform in these districts relative to a set of control districts. Then, leveraging reform exposure as an instrument for individuals’ registration status—and therefore possession of identity documents—I provide evidence on its consequences for access to public resources and exposure to taxation.

The results point to effects on access to resources of particular relevance for relatively wealthier citizens, such as higher education and state employment, with no effect on access to broad-based public goods, such as primary education. In turn, registration increases citizens’ direct tax payment. For the compliers induced to be registered by the reforms, registration creates substantial variation in access to a relatively narrow set of resources. Next, consistent with the stratified incidence of costs and benefits conditioning citizens’ decisions, I establish three results. First, fewer citizens complied with the reform in localities where overall levels of tax collection were higher or where the local incidence of taxation was particularly progressive.Footnote 2 Second, the local presence of narrow-based public goods (secondary schools), but not broad-based public goods (primary schools), positively predicts compliance. Third, indicative of citizens’ evaluation of these returns, individuals in targeted localities induced to register were differentially those born into the elite. I demonstrate the robustness of the results across specifications, datasets, and estimation strategies.

In so doing, this article speaks to two literatures. First, it relates to work on the informational dimensions of state capacity. As a recent literature shows, the state’s informational capacity lies at the core of common conceptions of state strength (Berwick and Christia Reference Berwick and Christia2018; Hanson and Sigman Reference Hanson and Sigman2021; Lindvall and Teorell Reference Lindvall and Teorell2017; Soifer Reference Soifer2013), and its aggregate variation affects a range of societal outcomes (Brambor et al. Reference Brambor, Goenaga, Lindvall and Teorell2020; D’Arcy and Nistotskaya Reference D’Arcy and Nistotskaya2017; Lee and Zhang Reference Lee and Zhang2017). If this capacity has such wide-ranging benefits, its persistently low levels across many developing country settings render it important—but mostly overlooked—to understand how it is built.Footnote 3 Because I argue the development of this capacity has distributive implications, its even expansion constitutes a political challenge as much as an administrative one. This political challenge implies that our understanding of the benefits of aggregate increases in informational capacity likely masks important heterogeneity in who benefits from a stronger state. The results in this article suggest a central role for economic inequality in conditioning how states invest in this capacity and to whom the benefits accrue.

Second, it relates to work on the distributive consequences of policy implementation. Prior work on the politics of civil registration has studied how the expansion of individually targeted social welfare programs has driven registration among previously excluded groups (Harbers Reference Harbers2020; Hunter and Brill Reference Hunter and Brill2016; Lund Reference Lund2008). In contexts where welfare systems are truncated, however, compliance with state demands often benefits the rich at the expense of the poor (Bastagli Reference Bastagli2009; Ferguson Reference Ferguson1999; Holland Reference Holland2017). The results here show how variation in citizens’ compliance decisions can lead even nominally universal policy instruments to have regressive implications.Footnote 4 This is substantively important because a billion people, half of them in sub-Saharan Africa, lack proof of legal identity in spite of sustained donor-led efforts (Gelb and Metz Reference Gelb and Metz2018). Understanding the returns to, and determinants of, registering with the state is a necessary component in evaluating these persistent failures to generate broad-based coverage.

REGISTRATION AND THE STATE

The informational capacity of the state is typically tied to its core challenge of revenue generation: states need information about their populations to tax them (Lee and Zhang Reference Lee and Zhang2017; Scott Reference Scott1998; Stasavage Reference Stasavage2020). Beyond taxation, theoretical models show how reductions in the extent of asymmetric information about citizens ameliorate an array of public administration and governance challenges (Banerjee Reference Banerjee1997; Ting Reference Ting2017). Given the high coercive costs associated with census enumeration (Soifer Reference Soifer2013), perhaps the most common method for states to collect information about their citizens is through identification and registration schemes (Breckenridge and Szreter Reference Breckenridge and Szreter2012; Caplan and Torpey Reference Caplan and Torpey2001).Footnote 5 I conceptualize citizens’ enrollment in such schemes as an informational transaction: citizens provide information about themselves, or their child, to the state in exchange for documentary evidence of their identity. Registration, therefore, reflects an instrumental decision rather than coercive imposition (Cohn and Dirks Reference Cohn and Dirks1988).

Citizens’ Decisions to Supply Information to the State

Citizens weigh the costs and benefits of registering with the state before deciding whether to comply with the state’s demands for information. These costs are both direct and indirect. Direct costs represent the short-run financial and time costs of registration, which are often significant in predominantly rural countries (Hunter and Brill Reference Hunter and Brill2016; Makannah Reference Makannah1981). Further, even when registration carries low de jure financial costs, high logistical costs necessitated by bureaucratic interaction and brokerage impose particular burdens on poorer citizens (Gupta Reference Gupta2012).

The indirect costs of registration comprise the often-uncertain downstream consequences of becoming legible to the state (Scott Reference Scott1998). Following Scott and a rich historical literature (Breckenridge and Szreter Reference Breckenridge and Szreter2012), recent studies validate the strong aggregate link between citizens’ supply of information to the state and their exposure to taxation (Brambor et al. Reference Brambor, Goenaga, Lindvall and Teorell2020; Lee and Zhang Reference Lee and Zhang2017; Sánchez-Talanquer Reference Sánchez-Talanquer2020). Several potential channels undergird this connection. For example, the administration of centralized direct taxes often imposes high informational demands on the state which are fulfilled by registration systems (Fjeldstad and Therkildsen Reference Fjeldstad, Therkildsen, Brautigam, Fjeldstad and Moore2008; Kiser and Sacks Reference Kiser, Sacks, Martin, Mehrotra and Prasad2009). Alternatively, because identity registration systems often undergird databases used across a range of government agencies, supplying information to the state for one purpose may not preclude its future use for extraction (Longman Reference Longman2018).Footnote 6

The benefits of registration are defined by how compliance affects access to resources, whether in the short term or the long term. International organizations point to a wide array of sectors and services whereby access potentially depends on civil registration with the state, including education, labor contracts, property rights, inheritance, and healthcare (UNICEF 2013). How binding these restrictions are, in practice, is often uncertain.Footnote 7

Distributive Incidence of the Returns to Registration

Whether, and from whom, states are able to solicit information is conditioned by the extent of bureaucratic capacity and political competition together shaping citizens’ expectations about the consequences of registering with the state. In a wide set of cases common to developing country contexts, where both bureaucratic capacity and democratic political competition are constrained, the incidence of these returns is especially economically stratified.Footnote 8

Bureaucratic Capacity

Akin to gatekeeping (Cooper Reference Cooper2002), citizens’ expected instrumental benefits of registration are shaped by the targeting and enforcement of exclusionary eligibility requirements in accessing particular goods, sectors, and services. The extent of the state’s bureaucratic capacity constrains its ability to control access to public resources and, hence, generate this demand for registration. Where such capacity is negligible, states are unable to regulate access to limited public resources and, hence, few citizens are incentivized to comply (Powell Reference Powell1981). At high levels of capacity, states can generate broad-based demand by conditioning access to a wide set of resources on the basis of registration status (Harbitz and Boekle-Giufrida Reference Harbitz and Boekle-Giufrida2009).

In intermediate cases, states can only selectively regulate access to public resources.Footnote 9 Controlling access to broad-based areas of service delivery imposes high costs of enforcement which may be untenable. Imposing a restriction on access to primary education in the absence of identity documents, for example, requires significant monitoring of the bureaucrats responsible for assessing eligibility. By comparison, it is less bureaucratically taxing to regulate access to more narrow-based areas of service delivery, such as higher education levels, which are both demanded by fewer citizens and likely to be located in areas where the state possesses preexisting bureaucratic infrastructure. Limitations in this capacity imply that the instrumental benefits of registration are more likely to center on areas of service delivery relevant for a narrow set of relatively wealthier citizens.

Political Competition

However, wealthier citizens face more pronounced indirect costs of supplying information to the state due to its potential consequences for taxation. High levels of democratic political competition render their decision particularly fraught. Because political leaders then have both some capacity to tax enrolled citizens and incentives to redistribute their fiscal resources, they cannot commit against redistributing the extracted taxes of wealthier citizens toward the poorer majority (Kasara and Suryanarayan Reference Kasara and Suryanarayan2015). Further, dampening the benefits of registration, strong democratic competition might disincentivize political leaders from the enforcement of policies restricting access to public resources (Gottlieb Reference Gottlieb2021; Holland Reference Holland2017). Last, to the extent that high competition implies frequent political turnover, in highly stratified settings, this might amplify citizens’ fears regarding the indirect costs, as well as sustained longer-term benefits, of complying with state demands (Padró i Miquel Reference Padró i Miquel2007).

When bureaucratic capacity is moderate and democratic political competition is weak, efforts to register citizens then have economically regressive consequences for the state’s informational coverage. First, the state’s limited extent of bureaucratic capacity renders the expected future benefits of registration more credible with respect to narrow-based public resources than broad-based ones. Second, in spite of the increased exposure to taxation they expect from complying with the state’s demands, limited competition mitigates the threat of the redistribution of wealthier citizens’ resources to the poorer majority.

This distributive incidence has two implications. First, states more easily structure informational transactions with higher economic status citizens to induce their compliance even ignoring the fact that these citizens face lower direct costs of registration due to their potential proximity to registration infrastructure, financial resources, or greater prior experience with the bureaucracy. Second, this incidence is incentive-compatible, and hence self-enforcing, to the extent that states fiscally benefit from inducing the taxation of wealthier citizens to a greater extent than poorer citizens.Footnote 10 Because expanding its informational coverage would either require the costly regulation of access to broad-based public resources, or resource-intensive investment in infrastructure to reduce the direct costs of registration facing poorer citizens, constrained states then face limited incentives to broaden their coverage given the returns from doing so.

Applicability of the Theoretical Framework

We should only expect these stratified implications in settings where economic status meaningfully predicts access to, and exclusion from, public resources. Importantly, this does not preclude contexts where distribution is often characterized as centering on non-economic divides. While a large literature is premised upon the ethnic basis of distribution across many developing country settings, recent work underscores how ethnic distribution is frequently equivalent to latent forms of economic class-based distribution (Alesina, Michalopoulos, and Papaioannou Reference Alesina, Michalopoulos and Papaioannou2016; Baldwin and Huber Reference Baldwin and Huber2010; Huber and Suryanarayan Reference Huber and Suryanarayan2016).

Figure A1 in the Supplementary Material, using cross-national data, demonstrates the strength of the relationship between exclusion from public resources according to social group status and exclusion according to economic status. As such, while non-economic cleavages can surely exert theoretically distinct effects on state-citizen interaction,Footnote 11 the distributive consequences of such state-building schemes should continue to hold in ethnically stratified settings to the empirically widespread extent that these cleavages overlap. Finally, the framework rests on the assumption that states are incentivized to tax their citizens and use information toward this end. In settings where fiscal incentives are sufficiently absent, such as rentier states, we should expect that such efforts have limited effects on the distribution of access to the state.

Empirical Implications

Economic inequalities in registration, access, and taxation are observed across a wide set of countries.Footnote 12 The theoretical framework implies that, moderated by capacity and competition, inequality in citizens’ registration is not simply epiphenomenal to these other inequalities in state–citizen interaction, but plays a constitutive role in entrenching and propagating them. Consistent cross-national evidence in Figure 1a documents the overall positive cross-country relationship between levels of economic development and civil registration rates. Figure 1b, however, illustrates how levels of registration mask important nonlinearities in the economic distribution of registrants. Inequality in citizens’ registration status expands as states initially develop their capacities, before shrinking as the full measure of citizens becomes registered by the state.Footnote 13 While suggestively consistent with the selective benefits of compliance inducing uneven distributions of citizens to enroll, it remains confounded. Most obviously, holding fixed its benefits and indirect costs, a similar pattern would be generated if wealthier citizens simply faced lower direct costs of registering with the state.

Figure 1. Income, Registration, and Inequality

Note: Registration is the share of citizens possessing birth certificates. Rich–poor registration difference is the percentage point difference in the registration rate of highest income quintile citizens relative to lowest quintile. RoW: rest of world; SSA: sub-Saharan Africa. Source: World Bank and UNICEF.

There are two key empirical implications of the theoretical framework which underlie this initial regressivity in the state’s informational coverage. First, citizens face only selective incentives to register with the state since doing so particularly facilitates access to narrow-based public resources while increasing exposure to taxation. Second, citizens’ local decisions whether to supply information to the state through registration schemes ought to depend on the balance of the benefits, in terms of access, and costs, in terms of taxation and redistribution, of doing so.

TANZANIA

The early postindependence period in Tanzania offers a useful case for testing these implications. Before providing quasi-experimental evidence in support of these implications, in this section, I first draw out features of the case salient to the theoretical framework and provide qualitative evidence on citizens’ decisions to register with the state.

Salient Features of the Tanzanian Case

First, with regard to its capacity, Figure A3 in the Supplementary Material plots the latent measure of state capacity from Hanson and Sigman (Reference Hanson and Sigman2021). This suggests that Tanzania’s capacity, in the period following independence in 1961, was slightly above average within sub-Saharan Africa and slightly below the global average.Footnote 14 This classification of moderate capacity is supported by the state’s partial regulation of access to public resources. With respect to education, the Tanganyika African National Union (TANU) regime was able to significantly control access to higher levels of education, whereas efforts to expand the provision of primary education were only weakly regulated and overseen (Court Reference Court1976; Resnick Reference Resnick1968). With respect to social security, the government exerted tight control over access to the formal sector, such as valuable state jobs and pensions, particularly in more urban localities (Tripp Reference Tripp1989).

Further, scholars underscore the state’s inability to effectively coerce its population: as Hyden (Reference Hyden1980) notes, the TANU regime initially “relied more on exhortation and persuasion than on compulsion” (76) to pursue its objectives. While the state became more coercive over time, the success of state-building schemes continued to rely on inducing the instrumental compliance of citizens. For example, it was only due to the state’s failure to induce rural citizens to relocate into organized villages that more coercive methods were attempted to resettle citizens (Barkan Reference Barkan1984). Other efforts to coerce citizens—such as to formalize urban workers (Diouf and Fredericks Reference Diouf and Fredericks2014; Tripp Reference Tripp1989) or employ tax field units (Bienen Reference Bienen1970)—were strongly resisted and often rendered unsuccessful.

Second, the Tanzanian case is defined by persistently low levels of political competition. Following TANU’s overwhelming electoral victory in 1962, the regime introduced an element of limited within-party competition while banning opposition parties (Bienen Reference Bienen1970; Cliffe Reference Cliffe1967). These low levels of political competition have persisted, with TANU and its successor party remaining dominant since independence. Importantly, in spite of this lack of meaningful political competition, TANU’s socialist orientation rendered it highly redistributive in its pursuit of a rural agrarian mode of development (Hyden Reference Hyden1980). Lee (Reference Lee1965) shows that individuals in the highest income bracket were subject to effective local tax rates twice as high as those in lower income brackets, whereas Huang (Reference Huang1976) shows that high income citizens faced effective direct tax rates on their income of around 30%, whereas those in the lowest income groups faced no direct taxation by the central state. This progressive tax incidence contrasted with most other developing country settings at the time (Coulson Reference Coulson1982).

Third, economic status has been enduringly predictive of access to public resources. Inheriting a relatively fragmented distribution of ethnic groups upon independence, TANU was able to implement nation-building initiatives which further reduced the salience of ethnicity as a cleavage structuring distribution (Glickman Reference Glickman1969; Mueller Reference Mueller1981). In its place, economic status became more strongly associated with distribution, with relatively high levels of economic inequality and much of the country’s wealth concentrated in very few districts (Coulson Reference Coulson1982; Tordoff Reference Tordoff1967). Figure A1 in the Supplementary Material highlights that socioeconomic cleavages are relatively more important for state access relative to social cleavages, but that neither of these measures are outliers either regionally or globally. Last, necessitated by its lack of natural resources and initially limited inflows from international donors, the state had clear incentives to extract taxation from its citizens (Due Reference Due1963).

Together, these features suggest that Tanzania is an appropriate, but nontrivial, case in which to examine the stratified consequences of states’ initial efforts to register their citizens. On the one hand, its moderate bureaucratic capacity afforded it some control over the regulation of access to public resources and policy implementation was conditioned by citizens’ willingness to comply. On the other hand, in spite of limited political competition, the orientation of the TANU regime posed a redistributive threat to economic elites.

Evidence on Citizens’ Registration Calculus

Government efforts to register the population in Tanzania began in 1894 and, as described in the research design below, intensified in the postindependence period (Kuczynski Reference Kuczynski1948). These efforts were rendered deeply incomplete—even today, under a fifth of the population possesses a birth certificate. A key reason for this failure is that citizens were acutely aware of the trade-offs they faced in supplying information to the state: as Kjekshus (Reference Kjekshus1974) concludes, “the Tanzanian citizen responds to a series of rational calculations of benefits and sacrifices connected with registration” (133). The key risk associated with registration during this period was that of taxation. The strength of the registration–taxation link inhibited birth registration in the colonial period, with the same officials often responsible for both registration and taxation (Walters Reference Walters2016; Wood Reference Wood2016). This link persisted: as studies of the 1965 election remark, “the most important reason, by far, for low registration was the spectre of taxation” (Harris Reference Harris1965, 31). Citizens’ fears were sufficiently extreme that the Vice President was forced to publicly declare that voter registration would not induce taxation, but low registration totals suggest that his promise was often considered non-credible (Bienen Reference Bienen1970; Kjekshus Reference Kjekshus1974).

The salience of this registration–taxation link was grounded in the primacy of individually targeted taxes inherited by the state upon independence (Kiser and Sacks Reference Kiser, Sacks, Martin, Mehrotra and Prasad2009). Due (Reference Due1963) shows that personal poll taxes, levied upon all adults, accounted for a substantial share of direct tax revenue collection in Tanzania, whereas Fjeldstad and Therkildsen (Reference Fjeldstad, Therkildsen, Brautigam, Fjeldstad and Moore2008) report that such taxes accounted for nearly all of Tanzania’s local revenues. Undermining effective administration, Lee (Reference Lee1965) notes that “when a male passes his eighteenth year, and thus becomes subject to local rates, cannot readily be determined, for no vital statistics are maintained” (39). An inability to observe the eligibility of citizens particularly inhibited tax collection in more urban localities which contained the majority of the country’s taxable wealth (Jensen and Mkama Reference Jensen and Mkama1968).

Qualitative evidence supports that citizens weighed these indirect costs against their expected benefits of registration. Hunter (Reference Hunter2015), for example, shows how registering and obtaining documentation “was understood to bestow particular rights and the capacity for claim making on its bearer” (134). These benefits, as noted by Powell (Reference Powell1981), were often diffuse especially for poorer citizens. Ethnographic evidence from Wood (Reference Wood2016) contrasts the benefits that registration with the state is supposed to generate for the poor with the reality that often “birth certificates and the benefits they are supposed to provide remain largely aspirational” (49).

Accordingly, sources point to a relatively limited set of services where access depends on proof of registering with the state. Access to higher levels of education is claimed to strictly depend on possession of a birth certificate,Footnote 15 whereas certificates are reported as being necessary for national health insurance schemes but not for more general access to healthcare (UNICEF 2013). Obtaining a passport officially requires the possession of a birth certificate, as does access to more recently developed national identity cards (ITU 2015). An additional set of potential uses relates to access to economic formality. Certificates are officially needed for applying to government jobs, for proof of citizenship for many private sector jobs and employment contracts, and for access to government pensions (Registrar General’s Office 2005). How binding these uses are in practice remains an empirical question.

Early postindependence Tanzania is, therefore, rendered a useful case by its moderate bureaucratic capacity, weakly competitive politics, and significant economic cleavages. In turn, qualitative evidence underscores that citizens carefully considered the trade-offs they faced in registering with the state, with descriptive evidence contrasting the salient threat of taxation against the relatively limited benefits of registration. This motivates the two key empirical predictions to be quantitatively tested in the context of government efforts to register the population: that registering with the state generates narrow benefits in access; and that citizens’ decisions to register are accordingly conditioned by the stratified local balance of these returns.

RESEARCH DESIGN

In this section, I describe the data sources and empirical strategy employed to test these expectations. In short, I leverage a policy reform to evaluate the consequences of registering with the state; then, I examine the determinants of registration by evaluating heterogeneity in citizens’ decisions to comply with the reform.

Data Sources

I employ two primary sources of data. First, I use data from an extract of the 2012 Population and Housing Census, which provides data from over 4 million people. Second, I use data on around 30,000 respondents from the National Panel Survey (NPS), a nationally representative household consumption survey.Footnote 16 Due to its much larger sample size, I draw outcomes from the census sample where possible. Descriptive statistics for the baseline census sample are provided in Table A1 in the Supplementary Material and for the NPS sample in Table A2 in the Supplementary Material.

Dependent Variables

The first outcomes for evaluating the consequences of registration relate to access to public goods. I focus on access to education and social security since prior scholarship on Tanzania makes clear the extent to which the central government exerted selective control over each sector (Coulson Reference Coulson1982; Court Reference Court1976; Resnick Reference Resnick1968; Tripp Reference Tripp1989). Using the census sample, I divide access to education into indicators for individuals having any primary, secondary, or university education. I divide access to social security into indicators for individuals having access to public national health insurance, a pension indicative of prior private sector employment, and a pension indicative of prior government employment.Footnote 17

The theoretical framework requires classifying outcomes, within these sectors, based on their particular utility for higher economic status citizens. To do this, I compute the partial correlation coefficient $ \rho $ (Wealth, DV) between a measure of economic status and each dependent variable.Footnote 18 Consistent with intuition and the qualitative evidence discussed above, this exercise suggests that we should expect effects of registration on access to higher levels of education more than basic education, and effects on access to formal sector social security through employment-linked pensions relatively more than access to redistributive health insurance funds.

Second, due to the absence of relevant variables in the census, I examine effects on tax payment drawing on the NPS sample. Using reported household expenditures, the primary outcome is an aggregate indicator for whether individuals paid any money to the government over the prior year. This is comprised of individual indicators for the payment of fees, local taxes, and taxes on income and property to the central government. Theoretically, the link between citizens’ identity registration and their tax exposure is likely to be stronger for centrally administered taxes, where states face more acute informational challenges, relative to locally administered taxes (Kiser and Sacks Reference Kiser, Sacks, Martin, Mehrotra and Prasad2009). Consistent with this, the $ \rho $ coefficients suggest that we should most strongly expect effects of registration on the payment of central government taxes.

Independent Variables

In each dataset, I observe whether individuals are registered, and hence possess a birth certificate, which is the primary independent variable of interest. Additionally, I observe the district and year of birth of each individual, which enables their assignment to the reform described below.

To investigate the second implication of the theoretical framework, I examine heterogeneity in citizens’ decisions to register as a function of the local net returns to doing so. First, I consider local variation in the levels of taxation using district-level data from Jensen and Mkama (Reference Jensen and Mkama1968): both the share of individuals paying taxes, which captures the extensive margin; and the amount of tax collected per taxpayer, capturing the intensive margin. To proxy for local redistributive pressures, I use data on the incidence of taxation from Lee (Reference Lee1965) measured by the difference in a district’s tax rate faced by individuals in the highest tax bracket compared with those in the lowest.Footnote 19 Second, I consider local variation in the presence of public goods using geolocated administrative data for primary and secondary schools which were founded prior to the mid-1960s.Footnote 20 Third, to assess the economic characteristics of registrants, I use data from the NPS sample relating to the educational attainment of a given respondent’s parents.

Estimation

To gain intuition for the empirical strategy, consider the following “naive” estimating equation:

(1) $$ \begin{array}{r}{y}_{itd}\hskip0.35em =\hskip0.35em {\beta}^{OLS}{\mathrm{Registered}}_{itd}+{\eta}_d+{\mu}_t+\gamma {X}_i+{\epsilon}_{itd},\end{array} $$

where $ {y}_{itd} $ is an outcome for individual i born in year t in place d; $ {\mathrm{Registered}}_{itd} $ is an indicator for whether i is registered, and hence possesses a birth certificate; $ {\eta}_d $ are the place of birth fixed effects; $ {\mu}_t $ are the year of birth fixed effects; $ {X}_i $ are the flexible controls for individual-level covariates, such as gender; and standard errors are clustered at the place of birth level. The fixed effects control for both time-invariant characteristics of individuals born in the same place and for temporal changes that affect individuals born across areas equally in a given year.

For $ {\beta}^{OLS} $ to identify the causal effect of registration, we must believe that $ {\mathrm{Registered}}_{itd} $ is assigned as-if randomly conditional on the controls. This is unlikely to be the case: even within a locality, wealthier citizens might have easier access to registration and other public resources, or might be more easily coerced both to register and pay taxes. Or, indicative of reverse causality, citizens already enjoying preferential access to resources might be more willing to comply with the state’s demands to register. In such cases, estimates of $ {\beta}^{OLS} $ are likely to be biased.

Compulsory Birth Registration Reforms

To overcome this inferential challenge, I leverage variation in exposure to a set of legal reforms relating to birth registration. Under Section 27 of The Births and Deaths Registration Act, first passed in 1920, the Tanzanian government can render birth registration “compulsory” for individuals born after a certain date in a given administrative area.Footnote 21

This legal reform was first applied in 1966 to make birth registration obligatory for citizens born after a given date in a set of localities comprising the “major towns” (Wood Reference Wood1971). The reform, publicized in newspapers throughout the year, was accompanied by changes to the price structure of registration to generate financial incentives to register births promptly and increased threats of punishment for noncompliance. Appendix A.1 of the Supplementary Material provides additional information on the reform. Intended as a demand-side shock for registration with the state, the reform was targeted at areas which contained just 5% of the Tanzanian population but a far higher share of its directly taxable wealth (Jensen and Mkama Reference Jensen and Mkama1968; Tordoff Reference Tordoff1967). The administrative councils in these areas were responsible for a greater share of their own tax revenue than more rural district councils, but their ability to generate revenues significantly underperformed (Dryden Reference Dryden1968).

As states wrangled with the informational voids they had inherited upon independence, similar government efforts were common across the region during this period (Breckenridge and Szreter Reference Breckenridge and Szreter2012; Dalberto and Banégas Reference Dalberto and Banégas2021).Footnote 22 Several former British colonies, such as Botswana, Ghana, Kenya, Sierra Leone, and Zambia, selectively targeted reforms to induce the registration of citizens living in urban, wealthier areas (Makannah Reference Makannah1981; Mehta and Assie Reference Mehta and Assie1979; United Nations 1985). Across former French colonies, such as Senegal and Côte d’Ivoire, states often enforced existing legal requirements to register with the state as a function of geographical proximity to urban registration centers (Barré Reference Barré2021; Brass Reference Brass1968; Cooper Reference Cooper2002). After this initial period, efforts to register citizens tended to stagnate (Padmanabha Reference Padmanabha1993).Footnote 23

Identification Strategy

I leverage citizens’ exposure to the 1966 reforms in Tanzania as a source of exogenous variation in individuals’ registration status in an instrumented difference-in-differences design. The geographically selective application of the reform generates potential spatial variation: individuals born in a “treated” area should be more likely to be registered than those born in a “control” area. By itself, this comparison is confounded by the general differences between treated areas and the rest of the country. As such, I combine this spatial variation with temporal variation: individuals born after the reform in one of the treated areas should also be more likely to be registered than those born before.

The identification strategy, ultimately seeking to instrument for individuals’ registration status, comprises two steps. The first step is a difference-in-differences design where I compare individuals born after (vs. before) the reform in places which were (vs. were not) treated by the reform. If the reform induced registration as intended, we should observe a larger difference in registration among cohorts born after versus before the reform in treated areas than in control areas. The baseline equation I estimate is the following:

(2) $$ \begin{array}{rl}{\mathrm{Registered}}_{itd}\hskip0.35em =\hskip0.35em {\beta}^{FS}{\mathrm{Reform}}_{itd}+{\eta}_d+{\mu}_t+\gamma {X}_i+{\epsilon}_{itd},& \end{array} $$

where exposure to the reform, $ {\mathrm{Reform}}_{itd} $ , is an indicator variable for whether i was born after the reform in one of the treated areas, and the other variables are as defined above for Equation 1. In the second step, I leverage this variation as a source of exogenous variation in registration to examine its causal effects in an instrumental variables setup. This implies a specification as follows, where I use Equation 2 as a first stage to predict registration, $ \hat{{\mathrm{Registered}}_{itd}} $ :

(3) $$ \begin{array}{r}{y}_{itd}\hskip0.35em =\hskip0.35em {\beta}^{IV}\hat{{\mathrm{Registered}}_{itd}}+{\eta}_d+{\mu}_t+\gamma {X}_i+{\epsilon}_{itd},\end{array} $$

where $ {y}_{itd} $ is a given outcome variable and the other variables are as per Equation 1 and Equation 2. Throughout, I define the place of birth fixed effects, $ {\eta}_d $ , to correspond to administrative units as existing prior to the reform (as discussed below) and cluster at this level. Following recent work on instrumental variables inference, I report p-values based on a clustered bootstrap (Lal et al. Reference Lal, Lockhart, Xu and Zu2021; Young Reference Young2022).Footnote 24

$ {\beta}^{IV} $ in Equation 3 estimates the local average treatment effect: the causal effect of registration over time among compliers induced to be registered by the reform. Then, to probe the determinants of registration, I examine heterogeneity in the first stage relationship. I do this by interacting the reform indicator in Equation 2 with the independent variables discussed above to evaluate how the local balance of these benefits and costs conditioned citizens’ compliance decisions.

Identification Assumptions

$ {\beta}^{IV} $ in Equation 3 is the primary coefficient of interest, which estimates a causal quantity if a set of identification assumptions are met. First, $ {\beta}^{FS} $ in Equation 2 must identify the effect of exposure to the reform on registration status. This primarily rests upon the assumption common to such difference-in-differences designs requiring that, absent the reform, rates of registration would have followed parallel trends over time in treated areas (where the reform was applied) relative to control (where it was not).Footnote 25

I maximize the plausibility of this assumption in two ways. First, through sample restrictions. In the baseline specification, I restrict the sample only to comprise cohorts born within 10 years of the reform and restrict the set of control birthplace areas. Control areas are restricted to be those which shared the same “parent district” as treated areas as defined prior to the reform. For example, Arusha town was treated with the reform and was nested within the larger Arusha district at the time of the reform. Treated areas as observed today, therefore, comprise the modern administrative district corresponding to Arusha town (Arusha Urban), whereas control areas comprise those districts corresponding to Arusha district (Arusha Rural and Meru districts).Footnote 26 For parsimony, I refer to these areas, for example, Arusha town and Arusha district, as distinct “districts” below since they correspond to modern districts. Second, it could be objected that other time-varying district-level characteristics are confounding the identification of $ {\beta}^{FS}. $ Therefore, in additional specifications, I add either region, or district, of birth-year of birth linear time trends to Equation 2. These time trends absorb either region-specific, or district-specific, trends in registration over time.

Supportive of the plausibility of the identifying assumption, Figure A6 in the Supplementary Material provides the visual evidence of parallel registration rates among individuals born in the period leading up to the reform. To more formally test this, in the analysis below, I include specifications where I add lead terms to Equation 2 reflecting i’s treatment status in years $ t+1 $ , $ t+2 $ , and so on. I find no effects on these lead terms, which would otherwise provide evidence against the parallel trends assumption by suggesting nonparallel pre-trends.

If $ {\beta}^{FS} $ identifies the effect of exposure to the reform then, under additional assumptions, this suggests the availability of a source of exogenous variation in registration status. First, relevance requires a strong first-stage coefficient $ {\beta}^{FS} $ , which I demonstrate empirically. Second, the exogeneity assumption requires that assignment to the instrument is as-if random, which I support using placebo tests in Table A7 in the Supplementary Material. Third, monotonicity requires the absence of individuals who would have been registered absent the reform but were not registered due to the reform. This assumption appears reasonable in this setting.

Finally, the exclusion restriction requires that an individual being born shortly after, versus shortly before, the reform in a treated district compared to in a control district must only affect relevant outcomes through the increased probability of their registration at birth. A threat to this assumption would be the existence of other policies affecting treated districts (but not control districts), during the same narrow time period, which independently affect the later-life outcomes of individuals born during this period through different channels. Appendix A.3 of the Supplementary Material provides supporting evidence toward the plausibility of this. In brief, a quantitative analysis of legislation during this period provides no evidence of other policies targeted specifically at the treated areas. Further, while the Arusha Declaration during this period heralded Tanzania’s transition to a rural model of development, (1) the sample restrictions exclude the most rural areas; (2) its immediate implications were relatively limited; and (3) it is hard to account for Arusha affecting outcomes in ways consistent with the observed results.

RESULTS

Table 1 estimates the first stage: the effect of variation in exposure to the reform on the probability of individuals being registered, and hence possessing a birth certificate, using Equation 2. In columns 1–3, I use the baseline specification of Equation 2, whereas in columns 4–6, I add 5 years of treatment lead terms to examine pre-trends, as discussed in the previous section. I linearly add the region of birth-year of birth time trends (columns 2 and 5) and district of birth-year of birth linear time trends (columns 3 and 6) for more demanding tests.

Table 1. Effect of Reform on Registration

Note: DV: respondent has a birth certificate. The sample is restricted to cohorts born within 10 years of the reform in the treated or control districts. The specifications are estimated using OLS including the district of birth and year of birth fixed effects and gender-district of birth controls. Exposure to reform is an indicator for being born after the reform in a treated district. Standard errors clustered at the district of birth level are reported in parentheses. * $ p<0.1 $ , ** $ p<0.05 $ , *** $ p<0.01 $ .

The estimate of $ {\beta}^{FS} $ in column 1 indicates that the reform led to a 6 percentage point (pp) increase in the probability that an individual is registered. This represents an effect size of nearly 50% compared with the outcome mean of 13%. The treatment effect is significant at the 1% level and associated with an F-statistic of 30, which suggests that it can be considered a strong instrument. The addition of substantially more demanding time trends only marginally decreases the coefficient estimate. There is little evidence, in columns 4–6, of nonparallel pre-trends.

The $ {\beta}^{FS} $ coefficient implies that 6% of the sample in the baseline estimation are compliers who were induced to be registered by the reform. I assess the robustness of these estimates in three ways. First, Table A4 in the Supplementary Material permutes the sample and estimation by: (A) varying the number of cohorts included in the analysis; (B) excluding individuals born in particular years; (C) adding additional control variables; (D) modifying the set of control districts; (E) permuting the fixed effects and clustering units; and (F) estimating the same first-stage relationship instead using the NPS dataset. Second, Table A6 in the Supplementary Material provides alternative estimation strategies, using either (A) local linear regression or (B) household-level fixed effects. Third, in Figure A7 in the Supplementary Material, I estimate a district-level jackknife of the first-stage coefficient to test for the presence of outlier districts driving the first-stage relationship (Young Reference Young2022). $ {\beta}^{FS} $ remains stably estimated across these tests.

Consequences of Registration

Under the plausibility of the identifying assumptions discussed above, I leverage this first-stage relationship as a source of exogenous variation in registration status. Across the outcome tables, the first panel reports the “naive” $ {\beta}^{OLS} $ coefficient obtained by estimating Equation 1, whereas the second reports $ {\beta}^{IV} $ , the primary coefficient of interest, obtained by estimating Equation 3. The $ \rho $ coefficient is reported at the bottom of each table to guide interpretation.Footnote 27

Access to the State

In Table 2, I report the effects of registration on access to the state. Panel I reports outcomes relating to access to education, whereas panel II reports outcomes relating to access to social security. First, considering effects on access to education, the $ {\beta}^{OLS} $ estimates show broad differences in access between those who are registered and those who are not: registered individuals are 11 pp more likely to possess primary education, 34 pp more likely to possess secondary education, and 10 pp more likely to have university education. Examining the $ \rho $ vector shows that economic status correlates most strongly with access to postprimary education. The causal $ {\beta}^{IV} $ estimates, accordingly, point to more selective benefits of registration on access to the state. These estimates show that registration causes no differences in access to basic education for the compliers induced to be registered by the reform. Registration does, however, cause striking increases in access to postprimary education, whether for secondary education or university, with effect sizes even larger than the $ {\beta}^{OLS} $ estimates.Footnote 28

Table 2. Effects on Access to the State

Note: DVs are all indicators. (1) has any primary education; (2) has any secondary education; (3) has any university education; (4) in a household accessing the National Health Insurance Fund; (5) in a household accessing a private pension; (6) in a household accessing a state pension. The sample is restricted to cohorts born within 10 years of the reform in the treated or control districts. $ {\beta}^{OLS} $ is estimated using Equation 1; $ {\beta}^{IV} $ is estimated using Equation 3. All specifications include the district of birth and year of birth fixed effects and gender-district of birth controls. Standard errors clustered at the district of birth level are reported in parentheses; bootstrapped p-values are reported in square brackets. * $ p<0.1 $ , ** $ p<0.05 $ , *** $ p<0.01 $ .

Second, considering effects on access to social security, the $ {\beta}^{OLS} $ estimates again show broad differences: registered individuals are 11 pp more likely to have access to the National Health Insurance Fund (NHIF), 12 pp more likely to have access to a private sector pension, and 11 pp more likely to have access to a state pension. The $ \rho $ vector suggests less pronounced differences compared with access to education, but that economic status correlates with access to pensions more strongly than with access to health insurance. In turn, the $ {\beta}^{IV} $ estimates provide stronger evidence of the causal effect of registration on access to pensions for the compliers, whether from the government or private sector, than on access to health insurance. While the point estimates are similar to each other and the $ {\beta}^{OLS} $ estimates, the estimate on access to health insurance is noisier than for the other two outcomes.Footnote 29

Taxation

In Table 3, using the baseline NPS sample, I examine the extent to which registration induces increased exposure to taxation among the compliers. The $ {\beta}^{OLS} $ estimates suggest that registration is associated with an 18 pp increase in the probability of making payments to the state. The $ \rho $ vector suggests that economic status more strongly predicts the payment of central rather than local taxes or fees to the government. While somewhat noisily estimated given the much more limited sample size of the NPS sample compared to the census, the $ {\beta}^{IV} $ estimates suggest a substantively large effect of registration on tax payment overall (column 1), which is particularly driven by increased payment of formal taxes to the central government (column 4). In Table A10 in the Supplementary Material, I estimate effects without restricting the set of cohorts included in the sample, which provides more precise, but very similar, point estimates.

Table 3. Effects on Exposure to Taxation

Note: DVs are all indicators. (1) in a household which has paid any tax in the last year; (2) in a household which paid fees in the last year; (3) in a household which paid local taxes in the last year; (4) in a household which paid taxes to the central government in the last year. The sample is restricted to cohorts born within 10 years of the reform in the treated or control districts. $ {\beta}^{OLS} $ is estimated using Equation 1; $ {\beta}^{IV} $ is estimated using Equation 3. All specifications include the district of birth and year of birth fixed effects and gender-district of birth controls. Standard errors clustered at the district of birth level are reported in parentheses; bootstrapped p-values are reported in square brackets. * $ p<0.1 $ , ** $ p<0.05 $ , *** $ p<0.01 $ .

Determinants of Reform Compliance

Consistent with the first implication of the theoretical framework, therefore, the results suggest that registration does not generate broad-based increases in access to public resources, but rather conditions access to public resources particularly relevant for relatively wealthier citizens. The magnitude of the $ {\beta}^{IV} $ coefficients implies that, for individuals induced to be registered by the reform, these targeted benefits in access are substantively large. In turn, registration increases the incidence of tax payment. The second implication of the framework posits that citizens, given the relative incidence of these returns, face a strategic decision in electing to register with the state in the first place. To provide evidence toward this, in the context of the reforms I leverage for the instrumental variables estimates, I probe local and individual-level heterogeneity in citizens’ compliance.

First, I examine how compliance with demands to register was conditioned by district-level variation in the threat of taxation at the time of the reform. In panel I of Table 4, I estimate Equation 2 while interacting the reform indicator with the local measures of taxation introduced above.Footnote 30 The results show that a 1-standard-deviation increase in the levels of taxation, whether on the extensive (column 2) or intensive (column 3) margins, reduces the extent of citizens’ compliance with the reform. Further, consistent with wealthier citizens’ concerns over the threat of redistribution, column 4 demonstrates that citizens’ compliance was lower in districts where the local incidence of taxation $ ({\tau}^{\mathrm{Max}}-{\tau}^{\mathrm{Min}}) $ was most progressive.Footnote 31 Estimating these interactions simultaneously suggests that the extensive and intensive margins may have been more important in conditioning compliance than the local incidence of taxation (column 5). Together, the increase in citizens’ registration induced by the reform is primarily driven by changes in localities where citizens, and particularly wealthier citizens, faced a relatively lower threat of taxation.

Table 4. Heterogeneity in Compliance with Reforms

Note: DV: respondent has a birth certificate. Panel I examines heterogeneity using local measures of taxation; Panel II using local measures of public goods. The sample is restricted to cohorts born within 10 years of the reform in the treated or control districts. District-level measures of tax levels are from Jensen and Mkama (Reference Jensen and Mkama1968); tax incidence is from Lee (Reference Lee1965); and local public goods are from administrative data. Regressions control for the interaction of Reform with standardized district income per capita and population density. All specifications are estimated using OLS including the district of birth and year of birth fixed effects and gender-district of birth controls. Standard errors clustered at the district of birth level are reported in parentheses. * $ p<0.1 $ , ** $ p<0.05 $ , *** $ p<0.01 $ .

Second, to provide evidence on how variation in the expected benefits of registration affected compliance, in panel II of Table 4, I examine similar heterogeneity using local variation in the presence of particular public goods existing prior to the reform. Using administrative data and guided by the estimates of $ {\beta}^{IV} $ in panel I of Table 2, I construct a measure of the local presence of narrow-based public goods in a district, using secondary schools, and broad-based public goods, using primary schools.Footnote 32 The estimates suggest that compliance with the reform is unrelated to the local presence of primary schools (column 6), and significantly positively related to the local presence of secondary schools (column 7). These effects continue to hold when I simultaneously include both interactions in column 8.

Third, I descriptively characterize the complier subpopulation who were induced to be registered by the reform, and for whom the instrumental variables estimates represent the causal effects of registration. In line with the prior results, we should expect that the individuals who complied with the reforms are those for whom these returns were positive in expectation. Following Angrist and Fernandez-Val (Reference Angrist, Fernandez-Val, Acemoglu, Arellano and Dekel2013), in Table 5, I assess descriptive characteristics of these compliers compared to the overall sample. I consider gender and the educational attainment of individuals’ parents, which offers a pretreatment proxy for the extent to which a given individual is born into a family with higher economic status.

Table 5. Complier Characteristics

Note: This table computes covariate means for baseline NPS sample (column 1) and compliers (column 2). Column 3 is column 2 divided by column 1.

This exercise suggests that the reform induced the registration of boys marginally more than girls: compliers are 6% more likely to be male than among the broader sample.Footnote 33 Comparisons using parental educational attainment, however, show striking differences: compliers are only 13% more likely to have parents with primary education, but over twice as likely to have parents with secondary education, and three times as likely to have parents with university education. The complier characteristics are consistent with the reform inducing individuals born into relatively wealthier families in these districts, for whom the returns to enrollment were positive in expectation, to be registered.

These results provide evidence consistent with the theoretical framework. While the instrumental variables estimates demonstrate that registration has distinctive causal effects on access to the state and exposure to taxation, the compliance analysis confirms that the variation in the stratified incidence of these costs and benefits, particularly relevant for the wealthy, conditions citizens’ decisions to supply information to the state.

CONCLUSION

A growing literature highlights the informational foundations of state capacity. In this article, I have examined a channel through which such capacity is initially built: through transactions whereby citizens trade information for increased access to the state. In contexts where citizens face high costs of registration, either due to the inaccessibility of infrastructure or through increased exposure to taxation, inducing compliance, therefore, relies upon the provision of expected benefits. These benefits, moderated by bureaucratic capacity and political competition, bias toward areas of particular utility for wealthier citizens. In turn, these citizens are induced to comply and accrue increased access—particularly to narrow-based public goods—while increasing their exposure to taxation.

Testing the implications of the argument in Tanzania, a series of reforms in the postindependence period highlight the nexus between registration and taxation and help to explain striking failures of the state to solicit information from its population over time. Leveraging variation in citizens’ exposure to these reforms in an instrumented difference-in-differences design, the results provide novel evidence regarding the dynamics of state-building efforts to build informational capacity. For the compliers induced to be registered by the reform, the benefits are substantial but targeted, with effects on access to narrow-based public goods in exchange for increases in tax payment. Supporting citizens’ underlying calculus in electing to supply information to the state, the local incidence of benefits and costs conditioned citizens’ willingness to comply with the reforms.

While the nature of the research design limits this evidence to one setting, the theoretical framework, existence of similar government efforts across a range of countries, and broader ubiquity of economic inequalities in registration, state access, and taxation, suggest that such dynamics are likely to have relevance elsewhere. Both theory and empirics suggest that a truncated state-building equilibrium limits the equalizing potential of such technologies to empower citizens to make demands upon the state. This equilibrium is just as much political in origin as it is administrative or bureaucratic: the theoretical framework implies that states often face only weak incentives to expand their informational coverage more broadly. Such expansions carry high resource costs—whether through regulating access to broad-based public resources or through investing in infrastructure to reduce citizens’ costs of enrollment—but also might risk disrupting the willingness of higher economic status citizens to comply with the state’s informational demands if they fear the redistribution of their resources.

Such technologies, instead, risk entrenching and propagating preexisting economic inequalities in state–citizen interaction when compliance, and its benefits, cannot be taken for granted. While much of the existing literature has tended to focus on the aggregate consequences of states’ capacities for societal outcomes, this suggests that the interaction between economic inequality and state-building processes might help to explain the otherwise puzzling underinvestment in states’ capacities over time. Further, given that variation in the informational transactions struck between state and citizen undergirds these inequalities, an increased focus on the local political economy of citizens’ decisions to comply with state-building efforts is needed to understand variation in both the levels and distribution of informational capacity across societies. To render the state’s informational coverage more even, it is not enough to decrease citizens’ direct costs of registering with the state: rather, citizens must receive sufficient incentives to make the decision worthwhile. As many developing countries rapidly introduce novel biometric technologies for the identification of citizens, an increased focus on these distributive dynamics is crucial for understanding the future political economic impacts of efforts to register the world’s poor.

SUPPLEMENTARY MATERIAL

To view supplementary material for this article, please visit https://doi.org/10.1017/S0003055423000394.

DATA AVAILABILITY STATEMENT

Research documentation and data that support the findings of this study are openly available in the American Political Science Review Dataverse at https://doi.org/10.7910/DVN/OM6ZUR.

ACKNOWLEDGMENTS

With thanks to the Kennedy Memorial Trust and Vogelheim Fund for funding. With thanks to the editors and three anonymous reviewers, Kate Casey, Anne Degrave, Torben Iversen, Kimuli Kasara, Imke Harbers, Horacio Larreguy, Melissa Lee, Evan Lieberman, Lucy Martin, Constantine Manda, Baruani Mshale, Michael Olson, Pia Raffler, Joan Ricart-Huguet, Abhilasha Sahay, Ken Shepsle and Joe Wong for their thoughtful comments, and participants at APCG Colloquium, APSA 2019, ASA 2019, Harvard, MIT Political Behavior of Development Conference 2018, MPSA 2019, NEUDC 2018, Twaweza Tanzania, and the Weatherhead Center for International Affairs for their feedback. Thanks also to representatives of the Tanzania National Archives, UNICEF Tanzania and the United Nations Archives who provided valuable assistance and insights.

FUNDING STATEMENT

This research was funded by the Kennedy Memorial Trust and the John C. and Katherine Vogelheim Hansen Research and Travel Fund for Africa.

CONFLICT OF INTEREST

The author declares no ethical issues or conflicts of interest in this research.

ETHICAL STANDARDS

The author affirms this research did not involve human subjects.

Footnotes

1 I focus on civil registration, through which individuals obtain birth certificates: even if other forms of identity documents exist, the possession of a birth certificate is generally viewed as the most important single document facilitating access to the state (AbouZahr et al. Reference AbouZahr, De Savigny, Mikkelsen, Setel, Lozano and Lopez2015).

2 This result aligns with prior work finding that states struggle to invest in fiscal capacity—because of the redistributive threat of taxation—when economic inequality is higher (Hollenbach and Silva Reference Hollenbach and Silva2019)

3 Some recent work considers the endogenous determinants of investments in capacity more broadly. For example, Sánchez-Talanquer (Reference Sánchez-Talanquer2020) considers elites’ decisions to register land, Christensen and Garfias (Reference Christensen and Garfias2021) consider electoral incentives to invest in capacity-building interventions, and Garfias and Sellars (Reference Garfias and Sellars2021) consider how centralizing investments are undermined by the weakening of local elites.

4 Civil registration reforms are typically considered progressive interventions: goal 16.9 of the United Nations Sustainable Development Goals, for example, aims to “By 2030, provide legal identity for all, including birth registration.”

5 As one Tanzanian newspaper wrote, “A census is a herculean exercise that entails long-term planning and high financial and manpower resources.” Comparatively, registration is a “cheap, and administratively convenient means” of “ensuring that we have a ready source of reference all the time, to set our priorities right and conduct our social and economic affairs intelligently” (Daily News, August 31, 1982). Survey data from sub-Saharan Africa suggest that a third of all citizens had attempted to obtain identity documents from the state in the prior year (Afrobarometer 2019).

6 Recent examples discussed by Clark (Reference Clark2018), including from India, Pakistan, and Uganda, illustrate how foundational identity system data are often shared across government agencies for purposes of tax collection. In turn, historical examples underscore the ways in which registration systems can become repurposed over time for the targeting of coercion and violence (Longman Reference Longman2018). More indirectly, if citizens instrumentally benefit from registration schemes, they may become more willing to comply with demands for taxation (Levi Reference Levi1988).

7 A review by DLA Piper (2016) reveals the ambiguity of these requirements: across 18 African countries, the overwhelming majority have ambiguous, or contradictory, legal requirements for the use of identity documents.

8 This stylized framework makes important simplifications relating to citizens’ economic status (higher or lower) and the basis of public resources (broad or narrow). While empirically justified by the cases considered in this article, these simplifications are potentially reductive in settings where economic status is less bifurcated or where the private provision of equivalent resources renders it challenging to define whether public resources are broad- or narrow-based.

9 Breckenridge (Reference Breckenridge2014), in his account of biometric identity systems in South Africa, underscores the tremendous costs of administering identity registration systems in constrained capacity settings when citizens face incentives to avoid the state’s extractive reach.

10 Importantly, this is consistent with states still benefiting to some extent from inducing the registration of relatively poorer citizens. As bureaucratic capacity increases, the threshold value of citizens’ income where the benefits of inducing their registration (through taxation) exceeds the costs (through regulating access) ought to decrease. For sufficiently high capacity states, these benefits likely exceed the minimal costs even absent strong distributive pressures. In such settings, robust states might additionally benefit from registration schemes for broader purposes of social control (Caplan and Torpey Reference Caplan and Torpey2001).

11 For example, ethnic status is likely to predict embeddedness in local networks useful for accessing resources, which might then dampen the incentives to register with the state (Kasara Reference Kasara2007). We might additionally expect that the salience of ethnic divides, by shaping their beliefs about downstream extraction, increases citizens’ indirect costs of registration.

12 While I focus throughout on sub-Saharan Africa, existing work on Latin America underscores that such inequalities are observed across many regions (Hunter and Brill Reference Hunter and Brill2016).

13 Indicative of the extent of their correlation, Figure A2 in the Supplementary Material replicates this inverted U-shaped relationship with respect to either levels of economic development or measures of state capacity on the X-axis.

14 This measure reflects important temporal variation in capacity, which was relatively low in the immediate postindependence period but significantly developed over the subsequent decades as the state exerted increased control over society.

15 One reason for this relates to the necessity of verifying the identity of individuals taking school leaving examinations (Suthar et al. Reference Suthar, Khalifa, Yin, Wenz, Fat, Mills and Nichols2019).

16 There are four rounds of NPS data in total, where the first three use the same set of respondents and the fourth uses a new sample. I employ the samples from Round 2 (2010–11) and Round 4 (2014–15) because Round 1 does not include a question on registration status and Round 3 comprises an identical sample to Round 2.

17 Private sector pensions are defined as those households with access to the National Social Security Fund or the Parastatal Pension Fund, whereas government pensions are defined as those households with access to the Public Service Pension Fund, Government Employee Provident Fund, or Local Authority Pension Fund.

18 More formally, I standardize and regress the outcome variable $ DV $ onto a standardized measure of economic status and the controls in Equation 1, with $ \rho $ corresponding to the coefficient on the economic status variable. These measures are based on indexes of asset ownership recorded in both the census and NPS samples.

19 Lee (Reference Lee1965) only reports exact tax rates by income group for around a third of all districts. To maintain reasonable coverage across the country, and since within-region differences are much smaller than across-region differences, I assign these tax rates to other districts in the same region when data are provided for at least one district in a given region.

20 Indicative of variation in the ease of their access and regulation, the data suggest that the average district had 12.4 primary schools in 1965 but just 0.5 secondary schools.

21 I exclude Zanzibar throughout and focus on mainland Tanzania, since Zanzibar has had an autonomous system of civil registration for over a century (Kuczynski Reference Kuczynski1948).

22 Figure A4 in the Supplementary Material plots the rapid increase in the share of African countries with formal institutions to register citizens in this period.

23 Suggestively consistent with the challenge of broadly inducing citizens’ registration, as well as the limited fiscal incentives the state faced to expand its informational coverage fully, Appendix A.2 of the Supplementary Material discusses the gradual expansion of these compulsory registration orders to more rural districts in Tanzania over time. I show that these subsequent orders, which took four decades before all citizens across the country had a nominal legal obligation to register with the state, were largely ineffective.

24 Specifically, I use the studentized clustered bootstrap as per Canay, Santos, and Shaikh (Reference Canay, Santos and Shaikh2021), although results are robust to instead resampling the non-studentized distribution of bootstrap coefficients (Young Reference Young2022).

25 Additionally, the identification of $ {\beta}^{FS} $ rests on the stable unit treatment value assignment assumption that individual i’s exposure to the reform does not affect j’s registration status. The robustness tests in Panel B of Table A6 in the Supplementary Material, which include household-level fixed effects, suggest that this no-interference assumption is plausibly satisfied.

26 Figure A5 in the Supplementary Material plots the location of these districts and Table A3 in the Supplementary Material maps relevant administrative units from the reform period to modern districts as observed in the outcome data sources as respondents’ districts of birth. The fixed effects used in the estimations reflect pre-reform administrative units (i.e., Arusha town or Arusha district, using the above example) rather than the corresponding modern administrative units (i.e., Arusha Urban, Arusha Rural, and Meru) to avoid potential issues arising from the use of posttreatment fixed effects.

27 Figure A8 in the Supplementary Material plots descriptive trends in the various outcome measures across treated and control districts across cohorts.

28 Figure A9 in the Supplementary Material provides the estimates of $ {\beta}^{IV} $ for access to education by specific grade of schooling. The figure, consistent with Table 2, shows the null effects of registration on access to all levels of primary education (P1–P7), but significantly positive coefficients on access to secondary education (S1–S4), advanced secondary education (S5 and S6), and university education. Table A8 in the Supplementary Material provides estimates relating to literacy to support the effects on access to education. The estimates suggest no effect on literacy in Kiswahili, the typical language of instruction for primary education, but strongly positive effects on literacy in English, typically taught at higher levels of education.

29 Table A9 in the Supplementary Material disaggregates the effects on social security access. The estimates show that effects on access to private pensions are driven by increased access to the National Social Security Fund (NSSF), which provides social security funds for individuals primarily with formal sector employment, and effects on access to state pensions are driven by increased access to the Public Service Pension Fund (PSPF) and Government Employee Provident Fund (GEPF), each of which indicate prior employment by the central state.

30 In all these analyses, I control for local income per capita, population density, and the interaction of each of these with the reform indicator. Doing so reduces concerns that the interaction terms I examine are simply picking up on overall local levels of development.

31 This result aligns with prior work finding that economic elites become more likely to undermine the state’s fiscal capacities as economic inequality increases (Hollenbach and Silva Reference Hollenbach and Silva2019).

32 I use an indicator for whether a given district had any secondary schools, since only a handful of districts had more than one secondary school during this period, and a continuous measure of the number of primary schools, since these were far more widespread.

33 Prior work on the gendered dimensions of civil registration demonstrates variation in the timing of registration (Harbers Reference Harbers2020) but provides relatively limited evidence on other gender biases in registration decisions (Bhatia et al. Reference Bhatia, Krieger, Beckfield, Barros and Victora2019).

References

AbouZahr, Carla, De Savigny, Don, Mikkelsen, Lene, Setel, Philip W., Lozano, Rafael, and Lopez, Alan D.. 2015. “Towards Universal Civil Registration and Vital Statistics Systems: The Time Is Now.” Lancet 386 (10001): 1407–18.CrossRefGoogle ScholarPubMed
Alesina, Alberto, Michalopoulos, Stelios, and Papaioannou, Elias. 2016. “Ethnic Inequality.” Journal of Political Economy 124 (2): 428–88.CrossRefGoogle ScholarPubMed
Angrist, Joshua, and Fernandez-Val, Ivan. 2013. “ExtrapoLATE-ing: External Validity and Overidentification in the LATE Framework.” In Advances in Economics and Econometrics: Volume 3, Econometrics: Tenth World Congress, eds. Acemoglu, Daron, Arellano, Manuel and Dekel, Eddie, 401–34. Cambridge: Cambridge University Press.Google Scholar
Baldwin, Kate, and Huber, John D.. 2010. “Economic versus Cultural Differences: Forms of Ethnic Diversity and Public Goods Provision.” American Political Science Review 104 (4): 644–62.CrossRefGoogle Scholar
Banerjee, Abhijit V. 1997. “A Theory of Misgovernance.” Quarterly Journal of Economics 112 (4): 1289–332.CrossRefGoogle Scholar
Barkan, Joel D., ed. 1984. Politics and Public Policy in Kenya and Tanzania. New York: Praeger.Google Scholar
Barré, Louise. 2021. “Disputing Parenthood at the Civil Registry in Côte d’Ivoire in the 1960s.” In Identification and Citizenship in Africa: Biometrics, Documentary State and Bureaucratic Writings of the Self, eds. Séverine Awenengo Dalberto and Richard Banégas, 239–53. London: Routledge.Google Scholar
Bastagli, Francesca. 2009. “From Social Safety Net to Social Policy? The Role of Conditional Cash Transfers in Welfare State Development in Latin America.” Technical Report 60. International Policy Centre for Inclusive Growth (IPC-IG).Google Scholar
Berwick, Elissa, and Christia, Fotini. 2018. “State Capacity Redux: Integrating Classical and Experimental Contributions to an Enduring Debate.” Annual Review of Political Science 21: 7191.CrossRefGoogle Scholar
Bhatia, Amiya, Krieger, Nancy, Beckfield, Jason, Barros, Aluisio J. D., and Victora, Cesar. 2019. “Are Inequities Decreasing? Birth Registration for Children under Five in Low-Income and Middle-Income Countries, 1999–2016.” BMJ Global Health 4 (6): e001926. https://doi.org/10.1136/bmjgh-2019-001926CrossRefGoogle ScholarPubMed
Bienen, Henry. 1970. Tanzania: Party Transformation and Economic Development. Princeton, NJ: Princeton University Press.Google Scholar
Bowles, Jeremy. 2023. “Replication Data for: Identifying the Rich: Registration, Taxation, and Access to the State in Tanzania.” Harvard Dataverse. Dataset. https://doi.org/10.7910/DVN/OM6ZUR.CrossRefGoogle Scholar
Brambor, Thomas, Goenaga, Agustín, Lindvall, Johannes, and Teorell, Jan. 2020. “The Lay of the Land: Information Capacity and the Modern State.” Comparative Political Studies 53 (2): 175213.CrossRefGoogle Scholar
Brass, William, ed. 1968. The Demography of Tropical Africa. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Breckenridge, Keith. 2014. Biometric State: The Global Politics of Identification and Surveillance in South Africa, 1850 to the Present. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Breckenridge, Keith, and Szreter, Simon, eds. 2012. Registration and Recognition: Documenting the Person in World History. Oxford: Oxford University Press.CrossRefGoogle Scholar
Canay, Ivan A., Santos, Andres, and Shaikh, Azeem M.. 2021. “The Wild Bootstrap with a ‘Small’ Number of ‘Large’ Clusters.” Review of Economics and Statistics 103 (2): 346–63.CrossRefGoogle Scholar
Caplan, Jane, and Torpey, John, eds. 2001. Documenting Individual Identity: The Development of State Practices in the Modern World. Princeton, NJ: Princeton University Press.Google Scholar
Christensen, Darin, and Garfias, Francisco. 2021. “The Politics of Property Taxation: Fiscal Infrastructure and Electoral Incentives in Brazil.” Journal of Politics 83 (4): 1399–416.CrossRefGoogle Scholar
Clark, Julia. 2018. “Public Sector Savings and Revenue from Identification Systems: Opportunities and Constraints.” Technical Report. The World Bank.Google Scholar
Cliffe, Lionel, ed. 1967. One Party Democracy: The 1965 Tanzania General Elections. Nairobi: East African Publishing House.Google Scholar
Cohn, Bernard S., and Dirks, Nicholas B.. 1988. “Beyond the Fringe: The Nation State, Colonialism, and the Technologies of Power.” Journal of Historical Sociology 1 (2): 224–9.CrossRefGoogle Scholar
Cooper, Frederick. 2002. Africa since 1940: The Past of the Present. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Coulson, Andrew. 1982. Tanzania: A Political Economy. Oxford: Oxford University Press.Google Scholar
Court, David. 1976. “The Education System as a Response to Inequality in Tanzania and Kenya.” Journal of Modern African Studies 14 (4): 661–90.CrossRefGoogle Scholar
D’Arcy, Michelle, and Nistotskaya, Marina. 2017. “State First, then Democracy: Using Cadastral Records to Explain Governmental Performance in Public Goods Provision.” Governance 30 (2): 193209.CrossRefGoogle Scholar
Dalberto, Séverine Awenengo, and Banégas, Richard. 2021. Identification and Citizenship in Africa: Biometrics, the Documentary State and Bureaucratic Writings of the Self. London: Routledge.Google Scholar
Diouf, Mamadou, and Fredericks, Rosalind. 2014. The Arts of Citizenship in African Cities: Infrastructures and Spaces of Belonging. New York: Palgrave Macmillan.CrossRefGoogle Scholar
DLA Piper. 2016. “Birth Registration: A Comparative Report Prepared for UNICEF.” Technical Report. UNICEF.Google Scholar
Dryden, Stanley. 1968. Local Administration in Tanzania. Nairobi: East African Publishing House.Google Scholar
Due, John Fitzgerald. 1963. Taxation and Economic Development in Tropical Africa. Cambridge, MA: MIT Press.Google Scholar
Ferguson, James. 1999. Expectations of Modernity: Myths and Meanings of Urban Life on the Zambian Copperbelt. Berkeley: University of California Press.Google Scholar
Fjeldstad, Odd-Helge, and Therkildsen, Ole. 2008. “Mass Taxation and State–Society Relations in East Africa.” In Taxation and State-Building in Developing Countries: Capacity and Consent, eds. Brautigam, Deborah, Fjeldstad, Odd-Helge and Moore, Mick, 114–34. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Foucault, Michel. 1991. The Foucault Effect: Studies in Governmentality. Chicago, IL: University of Chicago Press.Google Scholar
Garfias, Francisco, and Sellars, Emily A.. 2021. “When State Building Backfires: Elite Divisions and Collective Action in Rebellion.” American Journal of Political Science 66 (4): 977–92.CrossRefGoogle Scholar
Gelb, Alan, and Metz, Anna Diofasi. 2018. Identification Revolution: Can Digital ID Be Harnessed for Development? Washington, DC: Brookings Institution Press.Google Scholar
Giddens, Anthony. 1986. “The Nation-State and Violence.” Capital & Class 10 (2): 216–20.CrossRefGoogle Scholar
Glickman, Harvey. 1969. “Traditional Pluralism and Democratic Processes in Mainland Tanzania.” Asian and African Studies 5: 165201.Google Scholar
Gottlieb, Jessica. 2021. “Keeping the State Weak to Prevent Collective Claim-Making in Young Democracies.” Technical Report. Texas A&M University.Google Scholar
Gupta, Akhil. 2012. Red Tape: Bureaucracy, Structural Violence, and Poverty in India. Durham, NC: Duke University Press.Google Scholar
Hanson, Jonathan K., and Sigman, Rachel. 2021. “Leviathan’s Latent Dimensions: Measuring State Capacity for Comparative Political Research.” Journal of Politics 83 (4): 1495–510.CrossRefGoogle Scholar
Harbers, Imke. 2020. “Legal Identity for All? Gender Inequality in the Timing of Birth Registration in Mexico.” World Development 128: 104778. https://doi.org/10.1016/j.worlddev.2019.104778 CrossRefGoogle Scholar
Harbitz, Mia, and Boekle-Giufrida, Bettina. 2009. “Democratic Governance, Citizenship, and Legal Identity: Linking Theoretical Discussion and Operational Reality.” Technical Report. Inter-American Development Bank.CrossRefGoogle Scholar
Harris, Belle. 1965. “Tanzania Elections 1965.” Mbioni: The Monthly Newsletter of Kivukoni College 2 (5): 1557.Google Scholar
Holland, Alisha C. 2017. Forbearance as Redistribution: The Politics of Informal Welfare in Latin America. New York: Cambridge University Press.CrossRefGoogle Scholar
Hollenbach, Florian M., and Silva, Thiago N.. 2019. “Fiscal Capacity and Inequality: Evidence from Brazilian Municipalities.” Journal of Politics 81 (4): 1434–45.CrossRefGoogle Scholar
Huang, Yukon. 1976. “Distribution of the Tax Burden in Tanzania.” Economic Journal 86 (341): 7386.CrossRefGoogle Scholar
Huber, John D., and Suryanarayan, Pavithra. 2016. “Ethnic Inequality and the Ethnification of Political Parties: Evidence from India.” World Politics 68 (1): 149–88.CrossRefGoogle Scholar
Hunter, Emma. 2015. Political Thought and the Public Sphere in Tanzania. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Hunter, Wendy, and Brill, Robert. 2016. “‘Documents, Please’: Advances in Social Protection and Birth Certification in the Developing World.” World Politics 68 (2): 191228.CrossRefGoogle Scholar
Hyden, Goran. 1980. Beyond Ujamaa in Tanzania: Underdevelopment and an Uncaptured Peasantry. Berkeley: University of California Press.CrossRefGoogle Scholar
ITU. 2015. “Review of National Identity Programs.” Technical Report. International Telecommunications Union.Google Scholar
Jensen, Søren B., and Mkama, Jumanne. 1968. District Data, Tanzania, 1967. Dar es Salaam: Ministry of Economic Affairs and Development Planning.Google Scholar
Kasara, Kimuli. 2007. “Tax Me If You Can: Ethnic Geography, Democracy, and the Taxation of Agriculture in Africa.” American Political Science Review 101 (1): 159–72.CrossRefGoogle Scholar
Kasara, Kimuli, and Suryanarayan, Pavithra. 2015. “When Do the Rich Vote Less Than the Poor and Why? Explaining Turnout Inequality across the World.” American Journal of Political Science 59 (3): 613–27.CrossRefGoogle Scholar
Kiser, Edgar, and Sacks, Audrey. 2009. “Improving Tax Administration in Contemporary African States: Lessons from History.” In The New Fiscal Sociology: Taxation in Comparative and Historical Perspective, eds. Martin, Isaac William, Mehrotra, Ajay K. and Prasad, Monica, 183200. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Kjekshus, Herge. 1974. “The Voter Register.” In Socialism and Participation: Tanzania’s 1970 National Elections, eds. the Election Study Committee, 125–38. Dar es Salaam: Tanzania Publishing House.Google Scholar
Kuczynski, Robert René. 1948. Demographic Survey of the British Colonial Empire: East Africa, Vol. 2. Oxford: Oxford University Press.Google Scholar
Lal, Apoorva, Lockhart, Mackenzie William, Xu, Yiqing, and Zu, Ziwen. 2021. “How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice based on over 60 Replicated Studies.” Working Paper.CrossRefGoogle Scholar
Lee, Eugene C. 1965. Local Taxation in Tanganyika. Berkeley: Institute of International Studies, University of California.Google Scholar
Lee, Melissa M., and Zhang, Nan. 2017. “Legibility and the Informational Foundations of State Capacity.” Journal of Politics 79 (1): 118–32.CrossRefGoogle Scholar
Levi, Margaret. 1988. Of Rule and Revenue. Berkeley: University of California Press.Google Scholar
Lindvall, Johannes, and Teorell, Jan. 2017. “State Capacity as Power: A Conceptual Framework.” Technical Report. Department of Political Science, Lund University.Google Scholar
Longman, Timothy. 2018. “Identity Cards, Ethnic Self-Perception, and Genocide in Rwanda.” In Documenting Individual Identity: The Development of State Practices in the Modern World, eds. Jane Caplan and John Torpey, 345–58. Princeton, NJ: Princeton University Press.CrossRefGoogle Scholar
Lund, Francie. 2008. Changing Social Policy: The Child Support Grant in South Africa. Cape Town: HSRC Press.Google Scholar
Makannah, Toma J. 1981. “Methods and Problems of Civil Registration Practices and Vital Statistics Collection in Africa.” Technical Report 16. International Institute for Vital Registration and Statistics.Google Scholar
Mann, Michael. 1984. “The Autonomous Power of the State: Its Origins, Mechanisms and Results.” European Journal of Sociology 25 (2): 185213.CrossRefGoogle Scholar
Mehta, D. C., and Assie, J. B.. 1979. “A Programme for Measurement of Life and Death in Ghana.” Technical Report 1. International Institute for Vital Registration and Statistics.Google Scholar
Migdal, Joel S. 1988. Strong Societies and Weak States: State–Society Relations and State Capabilities in the Third World. Princeton, NJ: Princeton University Press.Google Scholar
Mueller, Susanne D. 1981. “The Historical Origins of Tanzania’s Ruling Class.” Canadian Journal of African Studies 15 (3): 459–97.Google Scholar
Padmanabha, P. 1993. “Review and Evaluation of UNFPA Supported Projects on Civil Registration and Vital Statistics.” Technical Report. United Nations Department of Economic and Social Development.Google Scholar
Padró i Miquel, Gerard. 2007. “The Control of Politicians in Divided Societies: The Politics of Fear.” Review of Economic Studies 74 (4): 1259–74.CrossRefGoogle Scholar
Powell, Nora. 1981. “Major Obstacles to Achieving Satisfactory Registration of Vital Events and the Compilation of Reliable Vital Statistics.” Technical Report 15. International Institute for Vital Registration and Statistics.Google Scholar
Registrar General’s Office. 2005. “Improving Services to Protect the Rights of the Most Vulnerable Children.” In Eastern and Southern Africa Conference on Universal Birth Registration, Mombasa, Kenya, 26–30 September 2005.Google Scholar
Resnick, Idrian N., ed. 1968. Tanzania: Revolution by Education. Dar es Salaam: Longmans of Tanzania.Google Scholar
Sánchez-Talanquer, Mariano. 2020. “One-Eyed State: The Politics of Legibility and Property Taxation.” Latin American Politics and Society 62 (3): 6593.CrossRefGoogle Scholar
Scott, James C. 1998. Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. New Haven, CT: Yale University Press.Google Scholar
Soifer, Hillel David. 2013. “State Power and the Economic Origins of Democracy.” Studies in Comparative International Development 48 (1): 122.CrossRefGoogle Scholar
Stasavage, David. 2020. The Decline and Rise of Democracy: A Global History from Antiquity to Today. Princeton, NJ: Princeton University Press.Google Scholar
Suthar, Amitabh Bipin, Khalifa, Aleya, Yin, Sherry, Wenz, Kristen, Fat, Doris Ma, Mills, Samuel Lantei, Nichols, Erin, et al. 2019. “Evaluation of Approaches to Strengthen Civil Registration and Vital Statistics Systems: A Systematic Review and Synthesis of Policies in 25 Countries.” PLoS Medicine 16 (9): e1002929. https://doi.org/10.1371/journal.pmed.1002929 CrossRefGoogle ScholarPubMed
Ting, Michael M. 2017. “Politics and Administration.” American Journal of Political Science 61 (2): 305–19.CrossRefGoogle Scholar
Tordoff, William. 1967. “Tanzania: Democracy and the One-Party State.” Government and Opposition 2 (4): 599614.CrossRefGoogle Scholar
Tripp, Aili Mari. 1989. Defending the Right to Subsist: The State vs. the Urban Informal Economy in Tanzania. Helsinki: World Institute for Development Economics Research.Google Scholar
UNICEF. 2013. Every Child’s Birth Right: Inequities and Trends in Birth Registration. New York: UNICEF Division of Policy and Strategy.Google Scholar
United Nations. 1985. “United Nations Handbook of Vital Statistics Systems and Methods. Volume II: Review of National Practices, Series F.” Technical Report. United Nations.Google Scholar
Walters, Sarah. 2016. “‘Child! Now You Are’: Identity Registration, Labor, and the Definition of Childhood in Colonial Tanganyika, 1910–1950.” Journal of the History of Childhood and Youth 9 (1): 6686.CrossRefGoogle ScholarPubMed
Wood, Christopher. 1971. “Gathering Vital Statistics in Africa: A Preliminary Report on the Recording of Births and Deaths in Tanzania.” Rural Africana 14: 61–2.Google Scholar
Wood, Summer. 2016. “Birth Rights: Birth Registration, Health, and Human Rights in Tanzania.” PhD diss. New York University.Google Scholar
Young, Alwyn. 2022. “Consistency without Inference: Instrumental Variables in Practical Application.” European Economic Review 147: 104112.CrossRefGoogle Scholar
Figure 0

Figure 1. Income, Registration, and InequalityNote: Registration is the share of citizens possessing birth certificates. Rich–poor registration difference is the percentage point difference in the registration rate of highest income quintile citizens relative to lowest quintile. RoW: rest of world; SSA: sub-Saharan Africa. Source: World Bank and UNICEF.

Figure 1

Table 1. Effect of Reform on Registration

Figure 2

Table 2. Effects on Access to the State

Figure 3

Table 3. Effects on Exposure to Taxation

Figure 4

Table 4. Heterogeneity in Compliance with Reforms

Figure 5

Table 5. Complier Characteristics

Supplementary material: Link

Bowles Dataset

Link
Supplementary material: PDF

Bowles supplementary material

Bowles supplementary material

Download Bowles supplementary material(PDF)
PDF 1.6 MB
Submit a response

Comments

No Comments have been published for this article.