Weber (1978) outlined an ideal type of bureaucracy characterized by several features, including that employees are recruited based on merit and make decisions based on codified rules, in an impartial manner. While Weber proposed that economic and technological developments are prerequisites for bureaucratic development toward this ideal, subsequent research has focused on how features of the bureaucracy affect economic development. In-depth case studies suggest that a well-organized, knowledgeable, and rule-following public administration fueled the economic development of several East and South-East Asian countries from the 1950s and onward (Amsden, 1992; Evans, 1995; C. A. Johnson, 1982; Kohli, 2004; Wade, 1990). Conversely, bureaucracies displaying “neo-patrimonial” modes of governance instead of Weberian features are proposed as a key reason for the underdevelopment of many Sub-Saharan African countries (Goldsmith, 1999; Sandbrook, 1986). In this article, we question, re-assess, and nuance the notion that a Weberian bureaucracy enhances economic growth.

The notion that Weberian bureaucracy and growth are causally linked is widely held among scholars, and several case studies have linked features of the bureaucracy to the economic development of particular countries. Still, the evidence base for a general effect from Weberian bureaucracy on growth from large-N studies is surprisingly thin. The latter studies consist of cross-section regressions on a handful of countries or panel regressions on short time series employing proxy measures that do not capture the relevant theoretical concept. If we employ the standards of inference currently used for other relationships involving observable macro-variables (e.g., democracy and growth; see Acemoglu et al., 2019), we cannot yet claim to know with a reasonable degree of certainty that Weberian features of the bureaucracy, in general, enhance growth.

This situation, we surmise, results from the lack of data that directly tap into Weberian bureaucracy with extensive time-series and geographical coverage. We therefore employ several new measures from the Varieties of Democracy (V-Dem; Coppedge et al., 2018a; Knutsen et al., 2019) project, which capture various features of Weberian bureaucracy from 1789 to 2017, globally.

These long time series allow us to include relevant information from the early period of modern history—an era that saw the building of professionalized bureaucracies and the take-off of modern economic growth, especially in Western Europe and North America (Maddison, 2001). They also allow us to check for heterogeneity in the relationship across time; some studies indicate that state institutions were less important for growth in this earlier period (Chibber, 2006; Sylla & Toniolo, 1991). Finally, they enable us to control for country-specific features that may bias the relationship, while ensuring sufficient variation on the slow-moving bureaucracy variables to keep standard errors reasonably precise.

Our results suggest that previous estimates on Weberian bureaucracy and growth from cross-country regressions have vastly overstated the relationship. Our panel models typically report positive, but modest, point estimates, which are mostly statistically insignificant at conventional levels. We conduct a battery of robustness tests and, for example, vary measures, estimators, and length of the panel unit; the lack of a clear relationship does not result from a particular specification choice. Yet, further analysis suggests that—if it exists—the effect tends to operate in the short term and is stronger in recent decades. The latter finding could, for instance, stem from bureaucracies becoming more important for growth as production technologies have become more complex, but it could also, in part, reflect that it is inevitably harder to measure Weberian features precisely in early years.

To summarize, while Weberian bureaucracy may ensure the effective implementation of various economic policies, “[s]tates with high capacity can pursue destructive economic policies” ( Johnson & Koyama, 2017 , p. 11). Arguably, the combination of a policy’s design and its effective implementation is what determines whether the policy enhances growth; a Weberian bureaucracy is only likely to ensure the latter condition. Thus, we need to confront the data before concluding that Weberianness enhances economic growth.

Finally, early work on bureaucracy and development focused on how bureaucracies, more generally, and in particular a sizable public sector, mitigate investments and efficiency—and thus growth—through different channels. These include incentives to promote red tape and excessive regulation, either by bureaucrats themselves or by politicians trying to control bureaucrats (e.g., J. Q. Wilson, 1989 ), opportunistic bureaucrats pursuing personal goals (e.g., maximizing size of their unit; Niskanen, 1971 ) that are incompatible with growth, and, more generally, information and delegation problems that create sub-optimal policies (e.g., Bendor et al., 2001 ; Gailmard & Patty, 2012 ).

Third, we remind that a Weberian bureaucracy is about organization and not about which policies are pursued. By being coherent and streamlined organizations with rule-following and competent staffers, Weberian bureaucracies can, in principle, implement any policy impartially and effectively. Indeed, if politicians, for some reason, decide to pursue monetary, fiscal, or industrial policies that mitigate growth, having a Weberian bureaucracy may exacerbate the negative effect of the policy, due to its effective implementation. 1 This possibility extends beyond theory. Historical examples of countries pursuing growth-retarding policies abound, either because politicians have legislated from misguided beliefs about what causes development, or because incumbents have had strong incentives to pursue particular economic policies despite knowing that they retard development (see, for example, Acemoglu & Robinson, 2012 ; Bueno de Mesquita et al., 2003 ).

Second, one key expectation linking Weberian bureaucracies to growth, as discussed, is the enhanced (de facto) protection of property rights, which, in turn, enhances investment. However, Greif (2006) and others have highlighted how other third-party enforcers than the state may serve similar functions, thus questioning the first link in the chain from Weberian bureaucracy via property rights to growth. Alternatively, various networks and other social arrangements may substitute for rule-of-law-based systems of property rights for safe-guarding investments, thus questioning the second link.

Some arguments above suggest important nuances on the expected relationship. Other considerations indicate that there may not be a strong net effect at all. For instance, growth—and especially long-term growth—may mostly result from total factor productivity change, induced by technological change, rather than physical capital accumulation (e.g., Helpman, 2004 ). If growth is not as clearly influenced by physical capital investments as several scholars who propose a relationship between bureaucracy and growth seem to presume, a key link in the causal chains laid out above is weakened or perhaps even obliterated.

A related argument has been made about differences between countries during early industrialization in Europe. Gerschenkron (1965) proposed that 19th-century state institutions were vital for promoting industrialization in relatively more “backward” countries, serving as substitutes for other (absent) prerequisites for development. The countries that were backward because they lacked the other prerequisites, but nevertheless experienced increased growth, did so because they engaged in state intervention in key economic areas.

More generally, having a Weberian bureaucracy might have become substantially more important for growth later in modern history, with the development of more complex production technologies (which are harder to monitor and manage), information technologies, and other sophisticated tools that administrations can employ in their work. Kohli (2004) , for instance, notes how state-directed development policies were relevant in post-colonial regimes, tying their varying success to differences in state capacity in different Asian, African, and South American countries. Moreover, Sylla and Toniolo (1991) argue that, except for state interventions in building railways, the state did not matter much for European industrialization in the 19th century. While playing indirect roles for economic development—for example, through protecting property rights and providing education—states were still fairly small relative to national economies, playing a negligible direct role, for example, in terms of public investments. Chibber (2006) compares early and late industrialization and argues that states mainly supported earlier (European) industrialization through tariff policies; state support was about “managing the effects” rather than “accelerating its pace.” In later years, states more actively developed “a more organized strategy of industrial policy and planning” ( Chibber, 2006 ). Such strategies required more well-functioning bureaucracies to succeed than the policies pursued in earlier phases of industrialization. Furthermore, the size of the public sector in the economy has grown substantially in many countries, particularly after World War II (WWII). Hence, the Weberian bureaucracy-growth relationship may have increased in strength across modern history.

Moreover, the effect of Weberian bureaucracy on economic development may depend on the time period under study. When reviewing research on the relationship between the state and economic growth, economic historians Johnson and Koyama (2017) point out that “[s]ustained growth began during the eighteenth century in England and in the nineteenth century in North America—prior to the development of a modern bureaucracy in either country” (p. 10). Other scholars have highlighted how an extensive, centralized state bureaucracy in prior centuries may have stifled political and economic dynamism, and thus long-term growth, via various mechanisms. For instance, centralized, non-European states were better able to resist pressures for colonization and “modernization” by European states (e.g., Acemoglu et al., 2002 ; Hariri, 2012 ), slowing capital accumulation and technology diffusion during the 18th and 19th centuries. However, the effects of having had early, centralized states may have changed following decolonization, predicting higher current state capacity and growth rates ( Bockstette et al., 2002 ; Foa, 2017 ).

There are, however, important nuances to the arguments presented above. First, if the effect flows mainly through physical capital accumulation, standard growth theory tells us that any effect of Weberian bureaucracy on gross domestic product (GDP) p.c. growth should materialize in the short to medium term, but have little bearing on long-term growth rates ( Acemoglu, 2009 ; Solow, 1956 ).

Third, states can alleviate physical, economic, and social insecurity by making life more predictable, and making predictions are at the heart of any economic calculus, be it investing in a business or in education ( Evans & Rauch, 1999 ). Two features of a Weberian bureaucracy—clearly delineated lines of authority/areas of responsibility with a certain bureaucratic autonomy and meritocratic recruitment/promotion—should increase predictability. An autonomous bureaucracy hinders arbitrary interferences by political leaders in bureaucrats’ decision-making. If so, prospective investors can more easily trust that the explicitly formulated laws and rules will be followed. Furthermore, a meritocratic bureaucracy enhances predictability because bureaucrats’ time horizons will be longer when their careers depend on their performance and not on political connections that may be less valuable after the next election (or coup). When bureaucrats anticipate a long career, short-term behavior, such as shirking or taking bribes, may be substituted for long-term behavior, such as working hard and following rules. Meritocracy and predictable career prospects thus contribute to an organization that is more apt at pursuing long-term goals (see also Evans & Rauch, 1999 ), which, in turn, influences how policies are implemented.

Moving to our second mechanism, Weberian bureaucracy may enhance competence among bureaucrats, which could (indirectly) enhance growth. Contrast a bureaucracy where recruitment and promotion are based on merit with one where they are based on familial ties, personal loyalty, or political connections. In the latter (“patrimonial”) administrations, bureaucrats have few incentives to develop their expertise. Empirical results corroborate that meritocratic-based recruitment contributes to better overall competence and performance of the bureaucracy ( Krause et al., 2006 ; Lewis, 2008 ; Rauch & Evans, 2000 ), lower corruption ( Dahlström et al., 2012 ), and less biased public policy knowledge ( Boräng et al., 2018 ). Competent bureaucracies could also spur growth because they “can help individual entrepreneurs overcome coordination problems . . . [and] turn informational resources into public goods in ways that increase the likelihood and effectiveness of investment” ( Evans & Rauch, 1999 , p. 753). Public agencies staffed with competent people can promote growth by providing growth-enhancing public investments, such as roads or railroads, more efficiently, and by providing reliable information to potential private investors on, for example, local business partners.

Nonetheless, if every non-simultaneous economic transaction would rely on the parties being certain that any future violation is detected and punished, transaction costs would be too high for any deal to be made. If, instead, these transactions could rely on expectations that a third-party enforcer will step in and arbiter potential conflicts impartially, transaction costs will be significantly lower. Thus, impartial bureaucracies can mold the long-term behavioral expectations that underpin economic transactions.

Impartial bureaucracies enter the story through the problem of enforcement. Property and contract rights are not primarily important as paper constructs but through how they enter people’s minds. For contract rights to work, parties to a deal must be expected to hold their promises. For property rights to function, people must share beliefs about the boundaries that separate one’s property from another’s. The actual workings of contract and property rights are thus based on certain behavioral expectations ( de Soto, 2001 ).

First, the Weberian features of rule-following and impartial decision-making may contribute to property and contract rights’ enforcement. Several key markets, including insurance and capital markets, require “non-simultaneous transactions, in which the quid is needed at one time or place and the quo at another . . . [and where] gains from trade cannot be realized unless the parties expect that the contracts . . . [are] carried out” ( Clague et al., 1999 , p. 186). Potential investors also require a guarantee that the fruits of such transactions are not expropriated, later on, by the state or other actors ( North, 1990 ). This is the straightforward theoretical case for the role of secure property rights in economic development.

If Weberian features of the state bureaucracy enhance growth, they should therefore contribute to either the formulation of policies that incentivizes investments and/or better implementation of these policies. We elaborate on three such mechanisms through which different features of Weberian bureaucracy can promote growth: Weberian bureaucracy may contribute to (a) enforcement of property and contract rights, (b) increase competence among bureaucrats, and (c) increase predictability. All these mechanisms may contribute to the formulation and implementation of policies that incentivize public and private investments, primarily in physical capital.

Any such relationship is presumably indirect. Institutional features typically matter for incentives to invest, educate, innovate, or adopt technologies developed elsewhere, because they shape how economic and other policies are formulated or implemented, which, in turn, incentivizes different economic actors to pursue particular courses of action (e.g., Bizzarro et al., 2018 ). Examples include particular education policies (e.g., recruitment of high-quality teachers) incentivizing young adults to stay in school, investment policies (e.g., transparent tax regulations) mitigating perceived risks for foreign investors, or intellectual property policies incentivizing entrepreneurs to invest in new technologies.

The key proximate causes of per capita (p.c.) economic growth, as recognized by growth economists, are physical capital accumulation, human capital accumulation, and technological development ( Acemoglu, 2009 ). Thus, a country’s public administration should matter for growth insofar as it incentivizes actors to invest in or otherwise enhance one of these “immediate determinants” of growth.

The Weberian ideal type of bureaucracy entails hierarchical organization with clearly delineated lines of authority and areas of responsibility, that decisions are based on clearly codified rules and made in an impartial manner, and that bureaucrats are meritocratically recruited, have expert training, and advance in the organization based on objective criteria ( Weber, 1978 ). Hence, Weberian bureaucracy is a description of how state administrations are organized and should be distinguished from outcome-centered concepts such as “state capacity” or “quality of government”. Whether having a Weberian bureaucratic organization promotes “good outcomes,” including good governance, are ultimately empirical questions ( Dahlström & Lapuente, 2017 ).

A final cautionary note on overtly trusting results from previous studies on bureaucracy and growth relates to measurement error in the dependent variable ( Fariss et al., 2017 ; Jerven, 2013 ; Martinez, 2018 ; Wallace, 2016 ). Assembling reliable statistics on national economic output over time is a complicated administrative task, and the reporting could be subject to strategic manipulation by political elites. A particular cause for concern is a possible relationship between Weberian bureaucracy and measurement errors in GDP. Let us assume, for example, that less Weberian bureaucracies are particularly vulnerable to elite manipulation and tend to over-report growth. If so, our independent variable is correlated with the error term, causing a downward bias in estimates of Weberian bureaucracy on growth. Alternatively, highly competent bureaucracies may be better at artificially inflating GDP figures so that manipulation is not easily detectable by data-collecting and processing organizations such as the World Bank and International Monetary Fund (IMF). This is consistent with recent speculation on bias in Chinese GDP figures ( Wallace, 2016 ). If so, standard regressions may over-estimate the relationship between Weberian bureaucracy and growth. We return to these issues below.

The more general macro-literature on institutions and growth has advanced methodologically in recent years, from being based on cross-sectional data to employing time-series and instrumental variables to address unobservable confounders and reverse causality. However, cross-country tests on the economic effects of bureaucratic quality, more specifically, have been restricted by shorter time intervals, given the lack of long time series on measures directly capturing features of the bureaucracy. 3 For example, International Country Risk Guide’s Bureaucratic Quality measure starts in the early 1980s, and the much-used measures of corruption from Transparency International and World Bank Governance Indicators have even shorter time series.

There are also sizable, related studies on how bureaucratic quality, governance, or “institutions,” more generally, affect growth (see, for example, Holmberg et al., 2009 ). Notably, Bockstette et al. (2002) construct a “state antiquity index” measuring historical existence of a state above tribal level, internal rule, and share of territory controlled by one regime. The measurement is done in 50-year increments, from Year 0 to 1950, and then aggregated up, discounting past experiences. This measure presumably correlates with current state capacity for different reasons, notably because state institutions take time to build. Running cross-country regressions, Bockstette et al. (2002) find that the index correlates positively with income in 1995 and growth from 1960 to 1995, suggesting a positive link between state capacity and current development. Subsequent work has used expanded versions of this measure. Putterman and Weil (2010) find a clearer relationship by measuring historical state presence at the location where current residents originate from (e.g., England for most Australians). Borcan et al. (2018) suggest a more complex, non-linear pattern; countries with very short state histories have slow growth, and very long state histories hinder development due to over-centralization and development of non-inclusive institutions.

Evans and Rauch (1999) is, to our knowledge, the only previous study that directly tests the impact of Weberian bureaucracy on economic growth. 2 The study is also the first attempt to collect quantitative data on different features of the public administration using expert survey data to gauge the level of “Weberianness.” Employing cross-country ordinary least squares (OLS) regressions, they find a positive relationship between degree of “Weberianness” and growth, and the estimated “effect” is substantial. Despite the innovative data collection, however, there are several methodological shortcomings of their study. It includes only 35 (mostly semi-industrialized) countries and draws on cross-sectional comparisons, which precludes any analysis over time and the control for country-specific factors that may influence both growth and the bureaucracy. Yet, given the prominent role that this study has played and continues to play in the literature—as of December 9, 2019, it has 1580 Google Scholar cites—we will start our empirical analysis by replicating its results.

Data and Benchmark Model

As Weberian bureaucracy is a multifaceted concept, we employ multiple measures, pertaining to different dimensions of the concept, from the Varieties of Democracy (V-Dem) dataset (Coppedge et al., 2018a).

Since V-Dem (as do Evans & Rauch, 1999) relies on expert surveys, data quality is a function of the quality of its experts. As detailed in their reference material, V-Dem applies high standards for recruiting their experts (see Coppedge et al., 2018b). They rely on multiple experts (at least five) per country-year and indicator; they draw primarily on domestic experts coming from or residing in the countries they code; they vet their prospective lists of experts substantially by standards of seriousness of purpose and impartiality; and, importantly, expertise in the particular field they are asked about is a key selection criterion. “This expertise,” according to V-Dem’s methodology document (Coppedge et al., 2018b, p. 20), “is usually signified by an advanced degree in the social sciences, law, or history; a record of publications; or positions in outside political society that establish their expertise in the chosen area.” Finally, V-Dem’s questionnaire consists of several sections, or “surveys,” including surveys on on elections, the executive or civil liberties. Experts are only assigned to provide answers for their particular field of expertise.

To address differential item functioning (different experts having different thresholds between response categories) and varying expert reliability, V-Dem transforms the raw ordinal expert ratings by a Bayesian item response theory (IRT) measurement model designed to improve cross-country and inter-temporal comparability (Marquardt & Pemstein, 2018; Pemstein et al., 2018). The end result is interval-level scores on the standard normal scale (with associated measures of uncertainty). Systematic assessments of the validity and reliability of V-Dem data also come to overall positive conclusions (e.g., Marquardt et al., 2019). For example, when meaningful comparisons can be made, the data correlate well with data from other sources. Furthermore, disagreement among experts is not egregious and correlates meaningfully with the complexity of the coding task. Although the assessments do not concern the exact indicators that we employ, several of these favorable validity and reliability assessments concern indicators of corruption (McMann et al., 2016), which, we surmise, should be even more difficult for experts to capture than the features of the bureaucracy that we attempt to measure. Nevertheless, we discuss and assess validity issues for our particular indicators below.

The partial exception to the recruitment rules and criteria concerns the historical (roughly pre-1900) part of the V-Dem time series. Given the relative paucity of historical experts—there are only a few true historical experts on, for example, 19th-century political history in Bavaria or Madagascar—these data mostly rely on one or two experts per country. These historical experts—who are often political historians—are also recruited based on documented expertise and seriousness of purpose, and questions pertaining to bureaucracies figured prominently in the historical data collection and recruitment decisions (Knutsen et al., 2019). Yet, one cannot exclude the possibility that some areas covered by the extensive survey are less well-charted territory for some particular experts. Combined with the relative lack of sources, especially for smaller countries, that will inevitably affect any historical data collection, this means that scores for the early years may be less reliable, even when relying on the expertise of historians. This, in turn, could contribute to attenuation bias; we return to this issue when discussing our results split by time periods below.

Our first indicator, which provides the most extensive time-series and country coverage, measures the extent to which countries have rigorous and impartial public administrations (v2clrspct, henceforth impartial bureaucracy). The question focuses on “the extent to which public officials generally abide by the law and treat like cases alike, or conversely, the extent to which public administration is characterized by arbitrariness and biases (i.e., nepotism, cronyism, or discrimination)” (Coppedge et al., 2018a, p. 157). The question wording relates to the de facto practice of public officials, not just de jure regulations. This is important because de jure changes are not necessarily followed by de facto changes in the bureaucracy (Schuster, 2017). This measure captures two key characteristics of Weberian bureaucracy—decisions abiding by clearly specified rules and decisions being implemented in an impersonal manner.

In Figure 1, we plot the relationship between impartial bureaucracy, averaged across 1970–1990, and the single score employed by Evans and Rauch (1999), assuming that the latter also applies to 1970–1990. For the 35 countries where the two measures can be compared, they are decently correlated (r = .60). Yet there are notable outliers, both countries ranking substantially higher on Evans and Rauch’s measure than V-Dem’s (e.g., Philippines, Democratic Republic of the Congo, Pakistan, and Haiti) and vice versa (Portugal, Israel, Costa Rica, Spain, and Hong Kong).

Our second measure taps directly into another aspect of Weberian bureaucracy, namely, meritocratic recruitment and promotion (v2stcritrecadm, henceforth meritocratic recruitment). The question asked to experts is as follows: “[t]o what extent are appointment decisions in the state administration based on personal and political connections, as opposed to skills and merit?” The clarification highlights that “[a]ppointment decisions include hiring, firing and promotion in the state administration. Note that the question again refers to the typical de facto (rather than de jure) situation obtaining in the state administration” (Coppedge et al., 2018a, p. 171).

This indicator is covered by the Historical V-Dem data collection (Knutsen et al., 2019), and thus extends back to 1789, but is only included in a random sample of 67 polities for the contemporary era (~post-1920) in V-Dem v.8.4

Figure 2 shows the time series of impartial bureaucracy and meritocratic recruitment for two countries included in our benchmark panel regressions in Table 2, namely, the United Kingdom and Uruguay. These time series (Figure 2) not only illustrate some more general points but also serve to validate and illustrate the data with well-documented countries that we know and which have diverged on patterns of bureaucratic development.

First, the major time-series shifts, for both cases, align with the “conventional wisdom” on when these bureaucracies were reformed or changed most rapidly. In the United Kingdom, the largest increase, for both measures, corresponds with the most significant change in the British public administration; in 1870, an Order in Council abolished patronage in the civil service by making competitive open examination mandatory for appointments (with some exceptions; see for example, Fry, 1969, pp. 34–69; MacDonagh, 1977, pp. 197–213; Silberman, 1993, pp. 350–397). Importantly, this reform was not only a declaration of intent on paper but resulted in changes also in practice. Data from the Civil Service Commission’s yearly reports show that the number of public offices that had open and competitive examinations increased substantially (Cornell & Svensson, 2019).

Second, countries often undergo periods of both “state building” and “state erosion” according to our two measures. While this is not captured by the United Kingdom’s (comparatively smooth) historical trajectory, it is well illustrated by Uruguay’s time series, which also fit well with historical accounts of bureaucratic development. The first upward shift in impartial bureaucracy concurs with the peace agreement after the “Guerra grande” in 1852 (López-Alves, 2000, pp. 81–84). Furthermore, the upward trend in 1876 coincides with the ascent of a military regime that modernized the state and strengthened property rights (Finch, 1981, p. 6; López-Alves, 2000, pp. 91–93), and the upward trend in 1897 coincides with the end of a rebellion, resulting in a power-sharing agreement between the Blancos and Colorados. The upward trend in 1904 marks the end of the last civil war, which implied further consolidation of the state, as territorial monopoly strengthened when the rebellion was defeated (e.g., López-Alves, 2000, pp. 71, 87). The year 1916 coincides with elections to a constitutional assembly, held in accordance with a new electoral law that guaranteed secret suffrage and universal male suffrage (Caetano & Rilla, 2005, pp. 159–160). According to Filgueira et al. (2003), the increasing influence of the opposition after the reforms of the political system in the beginning of the 20th century worked as a check against patrimonial practices.

As noted, our measure of impartial bureaucracy also displays dips in Uruguay, first in 1933 when democracy broke down after an autogolpe (there is then an upward shift that coincides with the “golpe bueno” in 1942; Caetano & Rilla, 2005, pp. 232–233). The next big dips in impartial bureaucracy come when state of emergency was declared in 1968 (Weinstein, 1975, pp. 117–118) and with the further curtailment of impartiality that occurred after the military coup in 1973. The measure also captures the increase in impartiality that came with the transition to democracy in 1985, implying, for example, the re-installment of 11,000 public officials who were dismissed during the military regime (Filgueira et al., 2002).

Third, Figure 2 illustrates that the different indicators, capturing different features of the bureaucracy, are far from perfectly collinear (they correlate at .59), sometimes displaying very different trends. In the United Kingdom, this is illustrated by further reforms of the functioning of the civil service in the late 1960s. These reforms followed in the wake of the Fulton report on civil service reform in 1968 (Fry, 1993), which did not change the pattern of meritocratic recruitment fundamentally. Similarly, the Uruguayan bureaucracy during the late 19th and early 20th centuries seems to have developed more impartial practices, despite the recruitment methods not changing much. The main parties did cooperate in enhancing politicization of the bureaucracy, which then possibly also had consequences for recruitment patterns (Filgueira et al., 2003). Notably, the famous pact in 1931 regulated, among other things, how the two main parties would share the right to appoint public employees (Caetano & Rilla, 2005, pp. 212–215; Weinstein, 1975, p. 69; V-Dem’s “meritocratic recruitment” registers an adverse change on December 31, 1930). The biggest upward shift in the indicator for meritocratic recruitment coincides with the democratization in 1985 and the related attempt to reform the system of civil service appointments (Filgueira et al., 2002, p. 12). In 1990, there were new reform attempts with a new law that foremost sought to decrease the number of positions but also to make recruitment more meritocratic (Guinovart, 2002). This law had a real impact in diminishing the number of public officials (Filgueira et al., 2003). There were reform attempts, also in the mid-1990s, for example as stipulated in the budget law of 1996, but these were largely unsuccessful in removing political criteria as an important feature of recruitment to the bureaucracy (Panizza, 2004). Thus, the Uruguayan case may illustrate that the indicator captures de facto and not only de jure changes.

We also assessed the V-Dem measures’ validity through convergent validation. One measure that is widely used for capturing concepts related to “Weberian bureaucracy,” such as “state capacity,” is Government Effectiveness from the World Bank Governance Indicators (Kaufmann et al., 2010). Our V-Dem measures correlate highly with Government Effectiveness; across 3,048 country-year observations from 1996 to 2016, the bivariate correlation with impartial administration is .83. The correlation with meritocratic recruitment is somewhat lower, at .74. Yet, it is unclear exactly what aspect of Weberian bureaucracy Government Effectiveness is capturing, as it is constructed from factor analysis on numerous variables.

Hence, for a more focused validation, we compare the V-Dem measures with measures from an expert survey conducted by the QoG Institute. The data are only measured in 2014, but, importantly, tap directly into relevant Weberian dimensions. Moreover, this is a specialized survey that recruits experts of public administration (Dahlström et al., 2015). Specifically, the QoG survey includes a question on impartial bureaucracy that should capture a similar concept as V-Dem’s impartial administration indicator from V-Dem (see Supplemental Appendix A). Indeed, these indicators are highly correlated (.77, V-Dem v.9; see Supplemental Appendix Table A-1).

The QoG survey also contains three indicators that closely tap into meritocratic recruitment. The first one refers directly to meritocratic recruitment, and the second and third ask whether recruitment based on political and personal connections, respectively, is common in a country’s bureaucracy (see Supplemental Appendix A). These indicators are all highly correlated (.74–.77, V-Dem v.9) with V-Dem’s Meritocratic recruitment (Supplemental Appendix Table A-1). Figure 3 presents scatterplots for, respectively, the indicators explicitly asking about impartiality in the administration and the indicators explicitly asking for meritocratic recruitment.

We also use two alternative measures from V-Dem, covering 1789–1920, for additional tests. These alternative measures capture distinct aspects of Weberian bureaucracy, allowing us to investigate in a more fine-grained manner which (if any) aspects of the bureaucracy are relevant for growth. One measure (v3struinvadm, henceforth autonomous bureaucracy) concerns rulers’ involvement in the state administration (Coppedge et al., 2018a, p. 217). The involvement of leading politicians in day-to-day administrative decisions signals that decisions are based on personal, politicized judgments rather than clearly codified rules—thus capturing similar aspects as the impartial bureaucracy indicator. Yet it also captures other key Weberian elements related to clearly specified areas of responsibility and a hierarchical organization with some autonomy. The second (v2strenadm, henceforth salaried bureaucracy) taps into the system of bureaucratic remuneration (Coppedge et al., 2018a, p. 171). As stressed by Weber (1978), this was not an evident feature of most state administrations in the 18th or early 19th century, when most officials instead “enjoyed the fruits of office, that is, to appropriate fees and perquisites flowing through it” (Mann, 1993, p. 446). During the 19th century, however, most European states started remunerating their state administrators by regular salaries.

For our benchmark specifications, we use GDP p.c. growth as dependent variable. We use the long time-series data from Miller (2015), extending back to the early 19th century. These (Purchasing Power Parity-adjusted, real) GDP data are based on data collected by the Maddison project and Gleditsch (2002). One concern is the particular endogeneity issue raised above, related to risks of systematic reporting bias in GDP, contingent on features of the bureaucracy. One way to assess this concern is to assume that satellite imagery of nighttime lights provides unbiased (though noisy) measures of economic output (Min, 2015). If true, the expectation that lower quality bureaucracies over-report their GDP figures should produce a negative correlation between bureaucratic quality and GDP, once controlling for lights.

As shown in Figure 4, however, this is not the case. Instead, when controlling for share of population living in unlit areas (in 2003), it seems that lower performing bureaucracies under-report GDP compared with higher performing ones. As GDP levels should not be equated with short-term growth, this is not foolproof evidence against the endogeneity bias sketched out above. The test does lend some prima facie evidence, however, to the effect that, if anything, our tests below risk over-estimating the effect of bureaucracy on growth.

Given the issue of potential reporting bias, we also test the imputed GDP time series of Fariss et al. (2017). These imputed data carry benefits of reduced measurement errors of various types, relative to extant GDP data, by being produced from a dynamic latent trait model on various data sources. The imputation of missing values—both for several countries and the early decades following 1789—should also mitigate sample-selection biases (Honaker & King, 2010), for example, if low-growth countries with non-Weberian bureaucracies more often miss GDP data.

Our benchmark is an OLS model including one of the above-described bureaucracy measures. We mainly use GDP p.c. growth as dependent variable but also estimate models using forward-lagged Ln GDP p.c. levels (note that this is equivalent to estimating GDP p.c. growth across the time period if we control for initial Ln GDP p.c.). The benchmark employs robust standard errors clustered by country to account for country-level serial correlation. We typically use year as time unit but also test versions with longer panel units (e.g., 5 years). We mainly lag independent variables five years behind the dependent variable to capture short- to medium-term effects but we also experiment with different lag-lengths.

We control for initial Ln GDP p.c., to account for income-convergence dynamics (Barro & Sala-i-Martin, 2004) and the possibility that economic development affects the makeup of the bureaucracy. We include time-fixed effects to account for global trends in the institutional makeup of administrations and global trends (e.g., due to technological change patterns) and shocks (e.g., global recessions) in GDP p.c. growth. We also include country-fixed effects to control for stable country-level features, including various cultural and geographic factors, which may simultaneously affect bureaucracies and growth.

We experiment with alternative controls in our robustness tests, adding, for example, democracy and natural resource dependence. Yet, we keep our benchmark parsimonious. We do so, first, to mitigate post-treatment bias—as discussed, a Weberian bureaucracy may affect growth via, for instance, strengthening property rights protection, and controlling for property rights would thus conceal a relevant indirect effect. Likewise, state building might influence subsequent attempts at democratization and democratic survival (e.g., Fukuyama, 2014), and we thus exclude democracy from the benchmark. Second, several potentially relevant controls, used only for robustness tests, have limited time-series coverage; including such measures therefore reduces our sample.