Moving Beyond the Influence of Neighbors on Policy Diffusion: Local Influences on Decisions to Conduct Property Tax Reassessment in New York

Abstract

Over the past few decades, research on policy adoption and diffusion has grown rapidly. Despite the relatively large number of publications, however, little attention has been paid to the important question of why a policy is differently implemented or diffused across governments. To answer this question and improve our understanding of local policy choice beyond widely cited neighboring influences, we closely examine the roles of three main policy actors—internal actors, external actors, and go-betweens—in the local policy diffusion process, drawing particularly upon property tax reassessment scenarios. In addition, we focus on nested institutional arrangements, including form of government and type of property tax assessor, that affect the policy decisions of internal actors. Using data on cities and towns in New York State for 1993-2010, we estimate event history models of property tax reassessment activities. Our findings reveal that regional interactions with neighbors that have already adopted the policy and top-down go-betweens through positive inducements can help facilitate property tax reassessment across municipalities. Reformed municipal governments in the council-manager form, along with appointed assessors, are also most likely to adopt reassessment policy frequently, compared with other institutional arrangements. Overall, this study advances the policy diffusion literature by exploring the roles of different influences through a more detailed, broader approach.

Keywords

policy diffusion institutional arrangements local policy choice property tax reassessment

Introduction

Who is involved in the policy adoption process and how a policy is being adopted are the controversial subjects, as well as salient empirical questions, that have long been addressed in the policy adoption and diffusion literature. According to Mohr (1969, p. 111), the propensity of innovation¹ (that is, the probability of policy adoption) is likely to rely on the interplay of motivation to innovate, obstacles against innovation, and resource availability. Among them, motivation to innovate has received increasing scrutiny. To pursue this line of inquiry, to date, much scholarly attention has been paid to such issues as the state lottery (Berry & Berry, 1990; Filer, Maok, & Uze, 1988; Jensen, 2003), state tax (Berry & Berry, 1992), education, welfare, and civil rights (Gray, 1973), charter schools (Renzulli, & Roscigno, 2005; Zhang & Yang, 2008), e-government ( Lee, Chang, & Berry, 2011), drug courts (Douglas, Raudla, & Hartley, 2015), and pay-for-performance (Ingraham, 1993).

Although the scopes and contexts of previous research vary across policy and public service areas, a significant question—why a policy is differently implemented or diffused across governments—still remains underexplored. Moreover, most studies have focused solely on policy adoption rationales rather than detailed, broader approaches of the policy diffusion process (Douglas et al., 2015; Füglister, 2012). In particular, it is notable that these studies have tended to rely heavily on the standard policy innovation model of Berry and Berry (1990) for their conceptual and analytical logic. In their seminal works on policy adoption, Berry and Berry (1990, 1992) have viewed both internal determinants of and (external) regional influences on a state’s likelihood of innovation together, which appears to make a great deal of sense for providing a better understanding of the dynamic process of policy adoption or change. They also have detailed the two main factors: While the internal factors represent political, economic, and social characteristics embedded in the government, the regional diffusion factors represent external pressure outside the government but in adjacent localities. Interestingly, between the two, it would appear that the existing literature has focused to a large degree on the influence of other jurisdictions (neighbors) who have already adopted a policy (here, external factors or actors).

Given that there is a relative scarcity of diffusion-oriented research beyond the existing standardized approach, it is necessary to make an in-depth examination and obtain additional knowledge of the complex policy diffusion process. Thus, more empirical research is required to examine other factors, beyond the widely observed internal and external factors (actors) affecting a policy adoption, that can increase or decrease the likelihood of policy diffusion in a broader manner. From this perspective, this study attempted to apply recent theoretical developments from policy adoptions in expanding the typical dichotomous characterization of policy innovation, to reach a more thorough understanding of policy diffusion.

First, we focused on another main factor referred to as go-betweens (other actors potentially influencing local adoption decisions), as described in recent scholarship (Douglas et al., 2015; Füglister, 2012; Graham, Shipan, & Volden, 2013; Karch, 2007). Specifically, the role of top-down go-betweens that exist in the hierarchical state-local governance relations in policy diffusion was analyzed in this study. In addition, we took a further step by looking at the dynamics of the nested institutional arrangements² that affect the policy decisions made by internal actors at the local level. As with McCabe and Feiock’s (2005) analytical approach, a model of nested institutions that proposes two-layered institutional differences influencing property tax reassessment policy was outlined in this research: (a) mayor-council versus council-manager government and (b) elected versus appointed property tax assessor. By focusing on the effect of nested institutional arrangements on local policy diffusion, we attempted to shed light on the determinants of local governments’ decision differentials across different governance structures.

This study essentially aims to answer the following question: how does a set of factors inherent in the policy environment correlate with local policy diffusion over time and further lead to different decisions about policy innovation across local entities? To explore the question with care, we paid attention to the adoption and diffusion of local governments’ property tax reassessment activity in New York State (NYS). Because property tax is the largest tax for local governments, and its assessment (revaluation) practice is one of the most salient and tangible local government decisions to their residents in that they are heavily associated with equity issues and production of the tax (Lee, Johnson, & Joyce, 2013, p. 161), understanding the dynamics inherent in the local decisions of property tax reassessment policy adoption appears to be worthwhile. Moreover, in the context of public finance and management, it is important for local governments to have an accurate prediction of their financial revenues, not only to smooth revenue volatility in the short term but also to achieve financial stability in the long term. Thus, from the closest standpoint of the citizens they serve, local governments and actors have enough reason to devote time to implementing reassessments of taxable properties frequently. It is expected that such policy decisions and the subsequent outcomes will help ensure that financial resources are efficiently monitored (managed) in response to socioeconomic and demographic changes in the cities and other localities.

This article is structured as follows: The next section begins with the background of property tax assessment policy and explains the case of NYS. The second section provides the conceptual framework of this research to examine the relationships between a set of factors and the likelihood of implementing frequent property tax reassessment at the local level. The third section discusses data collection and measurements for the analysis. The fourth section presents the empirical results. Finally, the article closes with a brief discussion of the findings and their implications for policymaking and management.

Background of Property Tax Assessment Policy and the Case of NYS

Given that property tax is basically levied on two types of property—land and permanent structures (mostly houses)—at large (Zodrow, 2001), it has a number of advantages as a local tax such as immobility, high visibility, stability, ease of administering (collecting), and a broad tax base. Yet it has also been considered politically vulnerable and traditionally regressive in a partial-equilibrium framework (Netzer, 1966; Wassmer, 1993; Zodrow, 2001).³ These unique characteristics of property tax point to a widely accepted recognition that property tax is the most unpopular tax as well as an unfair one (Eom, 2008; Fisher, 1996).

Property tax, unlike other taxes, requires assessment processes through which the taxable value of residential and commercial property is determined and monitored by assessors rather than observed from market transactions (Eom, 2008). According to Mikesell (1980), valuation is the heart of property tax administration and works on a cycle basis, thereby playing an important role in shaping assessment quality (uniformity), accompanied by (effective or not) tax rates. Because market values of properties change rapidly, especially when growth rates of properties are heterogeneous, the lack of reassessment is likely to generate lower assessment uniformity⁴ and entail significant discrimination⁵ regarding tax burdens. Therefore, it is possible that property owners lose the true market value of their property for that year and bear an unfair tax burden even if their properties have not actually increased in value ( Fisher, 2007; McMillen, 2013; Yinger, Borsch-Supan, Bloom, & Ladd, 1988).⁶ Hence, it is important for governments not only to evaluate local properties fairly (at a uniform percentage of market value) and accurately but also to administer the assessment policy effectively.

Recognizing the complex nature of property revaluation, a body of previous literature has empirically explored the determinants of property tax assessment uniformity. The findings revealed that reducing assessment errors (revaluation lag) and improving assessment uniformity (quality) may rely on, for example, the local economy, housing market conditions, and assessor characteristics (i.e., full-time vs. part-time or local vs. state or private assessors) (Bowman & Mikesell, 1978, 1989; Ross, 2013), the number of years of experience an assessor has (Propheter, 2016), the institutional types of assessors (elected vs. appointed assessors) (Bowman & Mikesell, 1989; Lowery, 1984; Ross, 2012), the quality and quantity of the personnel (sufficient staffing with well-trained, professional assessors) (Eom, 2008; Mehta & Giertz, 1996), or neighborhood characteristics (socioeconomic status) (Allen & Dare, 2002; Heavey, 1983). In addition, in a broader manner, maintaining fair and accurate property tax assessments can depend largely on a state’s institutional constraints on local governments, including the requirements for a specific reassessment cycle⁷ (e.g., annual, longer, or none) and the level of governments whose assessment functions. This viewpoint appears to be directly associated with whether local governments adopt an annual reassessment policy, how well the assessments are performed by assessors, and which are policy adoption or managerial capacity issues. When considered together, in the property revaluation practice, it seems that how to make the property tax (or value) assessment more effectively manageable matters and still continues to be controversial.

NYS has undertaken unique institutional arrangements pertaining to property tax assessments that significantly differ from those of other states, providing a valuable research opportunity. NYS has no legal provision for a specific reassessment cycle⁸ and, in contrast to southern and western states, most decisions regarding property tax administration are determined by local governments (International Association of Assessing Officers, 2000; Melnik & Cenedella, 2009).⁹ Although the number of assessing units has been recently reduced because of the county-level co-assessment practices induced by the state, cities, towns, and even some villages basically have their own assessment functions (particularly the property tax assessor selection method).

According to the NYS Department of Taxation and Finance (2015), municipal-level jurisdictions in NYS have the option of adopting a local law to retain elected three-member boards of assessors, a single appointed assessor, or a sole elected assessor (pursuant to NYS Real Property Tax Law [RPTL]: §310, §328, and §329).¹⁰ The law may require a mandatory or permissive referendum, or no referendum, on the replacement of the assessor type in each municipality. There has been a general trend of moving toward the appointment system from the traditional selection method of assessors based on election. As a result, it was reported that nearly 86% of the cities and towns in NYS are likely to have appointed assessor systems in 2010.¹¹ Therefore, the localities of NYS in terms of a property’s reassessment are markedly independent, with autonomous managerial power. This distinctive feature that hinders statewide full-value assessment is reminiscent of the tradition of local assessment autonomy, as a result of the historical heritage of colonial states (McClelland, 1965). Overall, it can be reasonably considered that, with respect to the property tax administration, NYS has a laissez-faire policy orientation.

Conceptual Framework

Main Factors (Actors) Shaping the Local Policy Diffusion Process: Internal, External, and Go-Betweens

As noted earlier, exploring the determinants of policy adoption and diffusion has been one of the central trends in the public administration and policy field over the past few decades. Scholars have conducted rigorous investigations into the contextual factors affecting the local policy process. Notably, Berry and Berry’s (1990) widely cited research on state lottery adoption first incorporated a comprehensive approach of policy adoption based on both internal determinants and regional diffusion models in their analysis. More recently, focusing on the larger policy environment, scholars (e.g., Douglas et al., 2015; Füglister, 2012; Graham et al., 2013; Karch, 2007) have suggested that three main policy actors—internal actors, external actors, and go-betweens—and their interactions are likely to play a critical role in deciding an innovation and shaping its diffusion process over time. In line with this viewpoint, this study paid close attention to the three factors (actors), each of which is discussed in further detail below.

First, it should be noted that a policy is likely to be chosen by “real people” with different views, preferences, capabilities, and goals, as mentioned by Graham et al. (2013, p. 684). In the policy environment, “people” basically refers to internal actors within governments pursuing an innovation. Although the actors (as individual decision makers) who affect local policy adoptions largely include the electorate, politicians, appointed officials, interest groups, and a local-level jurisdiction (Douglas et al., 2015; Graham et al., 2013), policy choices tend to be finally made by local officials or policy makers. In view of this, by drawing upon the property tax reassessment scenarios, this study focused on local governments and property assessors as the main internal actors who decide and operate reassessment policies.

Second, external actors represent neighboring governments that are in close geographic proximity and have already made the policy choice. Starting with Walker’s (1969) policy diffusion research, the so-called (external) regional factor pertaining to the influence of neighbors has been largely considered a catalyst for facilitating policy diffusion. Berry and Berry (1990, 1992) argued that regional influences, measured by the presence of neighboring states that have previously (or recently) adopted a particular policy, are likely to play an important role not only in motivating public officials to make an operational decision but also in overcoming difficulties and risks inherent in the innovation. Through focused research, such neighboring influences leading to the policy diffusion in a jurisdiction appear to be partly a result of citizen pressure ( Lee et al., 2011; Zhang & Yang, 2008), communication among the members of a system (Rogers, 2003), social learning (Berry & Berry, 1990; Meseguer, 2005; Mintrom, 1997; Mooney, 2001), competition (Berry & Berry, 2007; Karuppusamy & Carr, 2012), and leadership (Walker, 1969). Of course, one could argue that a policy adoption may occur or its diffusion may be enhanced depending on how well the policy conforms to social and cultural norms and whether it is seen to be beneficial in the jurisdictional setting (Jensen, 2003; Mooney, 2001). Yet a body of literature on policy adoption and diffusion has argued that the greater the number of previously adopting neighbors, the greater the likelihood that governments will adopt the policy over time. In light of this, this study posits that neighboring localities’ statuses and regional interactions have a significant association with property tax reassessment activity in a local government. Because residents and their property-related behaviors tend to be intensively intertwined with those of neighboring cities and towns through their housing markets in a real-world setting, we claim that a local policy diffusion process reflects the influence of neighbors.

In addition to the internal and external actors described above, we posit that “go-betweens” play a critical role in shaping local policy diffusion. Go-betweens refers to other actors who can potentially influence the policy adoption decision across local jurisdictions. Furthermore, it can be divided into two subactor groups: top-down go-betweens and epistemic go-betweens (Douglas et al., 2015). The former group refers to a federal or state government’s pressures on lower level jurisdictions, which demonstrate the coercion mechanism¹² (based on the so-called “carrot and stick” approach) toward the policy diffusion. On the contrary, the latter group includes professional associations (e.g., national organizations, conferences, and think tanks) that help share each other’s experiences when adopting the policy, as well as interest groups and newspapers that help obtain the policy-related information (Füglister, 2012; Karch, 2007). With respect to the influences of top-down go-betweens, as noted earlier, localities in NYS have implemented their property tax reassessment activities by themselves without a mandatory statewide cycle. Until recently, the state laws did not specifically incorporate an article making the adoption of the annual reassessment policy by the local government compulsory.¹³ Instead, it can be reasonably assumed that there has been a statewide guideline or recommendation to motivate local governments to conduct the annual revaluations of property values and the subsequent tax rates. NYS has generally used various statewide positive inducements to improve their municipalities’ assessment quality. For example, the NYS Department of Taxation and Finance established a coordinated assessment program, in which two or more municipalities coordinate their assessing functions by sharing an assessor or using the same assessment schedule. This program started in 1995, along with state-aid provision to the participants. Through the Excellence in Equity Awards, established in 1999, NYS also provided financial incentives based on annual or triennial aid to municipalities conducting the reassessments on a regular basis. In addition, given that the U.S. property assessors typically have membership in more than one of the national or regional professional associations and conferences, the epistemic go-betweens are expected to play a role in the training and education of the assessors, regardless of whether they are elected or appointed.¹⁴

An Additional Factor in the Local Policy Diffusion Process: Nested Institutional Arrangements

Although there is a large body of literature on policy adoption and diffusion that has examined who is involved and how a policy is being adopted, a scholarly approach exploring in detail why a policy is differently implemented or diffused across local governments is lacking. For this reason, it is important to expand our viewpoint to investigate the complexities of a policy environment in which local governments are nested at the macro level (Douglas et al., 2015). In this study, therefore, particular attention was paid to an additional factor—institutional influences—that can affect the willingness of local public officials or policy makers to adopt an innovation.

According to Clingermayer and Feiock (2001) and North (1990), institutions can be defined as humanly devised formal or informal constraints affecting individual incentive structures, accompanied by human actions (interactions). In particular, as Williamson (1985) suggested, unlike market governance, political governance and institutions, inherent in hierarchies and strict rule-based structures, help reduce uncertainty and opportunistic behaviors embedded in human transaction activities and further lessen transaction costs (e.g., monitoring cost). McCabe and Feiock (2005) agreed with the importance of institutions, stating that “[i]nstitutions and their effects may be best understood as nested systems” (p. 650). From the new institutionalism perspective, lower level, substantive rules work within a structure of higher level, constitutional rules, and local internal actors’ policy decisions are influenced by both constitutional- and substantive-level institutions (rules) (McCabe & Feiock, 2005; Ostrom, 1990). Consistent with this viewpoint, we could expect that the extent to which local governments’ willingness to adopt a policy depends on the nested institutional arrangements.

Notably, among diverse local political institutions, form of government¹⁵ has been widely explored in previous studies. It has long been acknowledged that form of government, as a constitutional-level rule addressed in municipal charters, specifies that either an elected mayor or an appointed professional manager owns the legal authorities in policy making (Clingermayer & Feiock, 2001; Svara & Watson, 2010; Zhang & Feiock, 2010). Given the current constitution-driven governance structures, local actors are likely to face two distinctive incentives—high-powered and low-powered—in the way of aligning their interests with those of citizens. In other words, local governments’ choices and behaviors pertaining to certain policies depend on whether the municipal’s constitutional-level institutions create high-powered or low-powered incentives (McCabe & Feiock, 2005). In practice, executive officials in mayor-council governments tend to be motivated by high-powered incentives, such as politicians’ desire for reelection, thereby increasing the likelihood of reflecting constituents’ preferences for policy (Bae & Feiock, 2004; Frant, 1996; MacDonald, 2008). Because of such political opportunism, mayor-council governments more likely value short-term visible outputs or ways to promote allocative efficiency while responding to voters’ demands in the jurisdiction. Moreover, as in previous studies (e.g., Kwon, Berry, & Feiock, 2009; Nelson & Svara, 2012; Zhang & Yang, 2008), elected executives are more politically risk-averse, and therefore sometimes become late adopters or nonadopters of an innovative policy and practice compared with appointed executives. On the contrary, given relatively fewer political conflicts of interest and greater professional motivation in the governance setting, executive officials more likely face low-powered incentives in operating policies (Carr, 2015; Svara, 1990). In cases where a local government has weaker mayor power and its significant policy-making processes are mostly implemented by professional administrators hired by a council, it is less likely to pursue political and financial incentives. This seems to pertain to the council-manager form of local governments, known as a progressive reformed government based on the separation of politics and administration, which explicitly produces a nonpartisan, efficient, and business-like regime with professional administrators (Lineberry & Fowler, 1967; Nelson & Svara, 2012). As such, it can be reasonably assumed that council-manager governments are more inclined to respond to achieve productive efficiency gains rather than behave opportunistically for individual gains in the use of public money (McCabe & Feiock, 2005). More specifically, rather than focusing on narrow issues or adopting policies that provide short-term political benefits, appointed executives are more likely not only to take risks with new ideas but also to pursue the long-term preferences of local residents (Carr, 2015; Clingermayer & Feiock, 2001; Schelling, 1960). Such results appear to be in accordance with previous studies (Hawkins & Feiock, 2011; Kwon et al., 2009; Zhang & Yang, 2008). Taken together, it is likely that, compared with elected executives, appointed executives may be less afraid of the risks of policy adoptions and more willing to operate innovative programs and practices.¹⁶

Moreover, the proposition on institutional arrangement differentials explained above can be extended to apply to the impact of assessor types in the property tax administration. As McCabe and Feiock (2005) and Ostrom (1990) pointed out, substantive-level institutions (rules) tend to deal with operational decisions in the form of a specific policy (e.g., taxation). In line with this approach, this research views the type of assessor (elected vs. appointed) as a substantive rule affecting local policy choices. In addition, given that local assessors, as one of the main internal actors, are responsible for monitoring property regularly and allocating available financial resources fairly (Eom, 2008; Mehta & Giertz, 1996), their property tax reassessment activities are considered a significant and specific policy innovation across local governments.

As previously discussed, municipalities in NYS have their own property assessment standards, and each city or town is able to choose an elected or appointed assessor system. Therefore, we naturally differentiated elected and appointed assessors in the institutional context of the manner of local assessor selection. Furthermore, by incorporating the dichotomy between high- and low-powered incentives embedded in the public governance structure into the current assessor institution of NYS, we predicted that the two different types of assessors exhibit distinct incentive structures in their policy decision-making processes. Specifically, elected assessors tend to have high-powered incentives in policy decision making, thereby being more responsive to constituent pressure. On the contrary, appointed assessors’ decisions on property reassessment are more likely to be driven by their own administrative viewpoint rather than the political interests of voters, because their mostly low-powered incentives are less sensitive to political pressures from house owners and taxpayers. In this respect, it can be hypothesized that appointed assessors are more likely to act in favor of innovative policy adoption than elected ones are.

Considering a combination of nested institutional arrangements in NYS municipalities, we concluded that the main differences in policy adoption across local governments center on whether municipalities have traditional (mayor-council) or reformed (council-manager) governments and operate their property assessment practices with elected or appointed assessors. Consequently, the following assumption can be drawn: Municipalities, based on the form of council-manager governments and having appointed assessors, are more likely to adopt a property tax reassessment policy more frequently than others, by substituting high-powered incentives with low-powered ones.

Data and Method

Data Description

The context for our study is local governments’ property tax reassessment activities. The unit of analysis is cities and towns known as general-purpose local governments, as well as property tax assessment units in NYS. For the empirical analysis, we collected data on each city’s and town’s reassessment activities, along with its institutional, financial, and socioeconomic profiles for an 18-year period (1993-2010). The data sources for constructing variables include the Office of Real Property Tax Service in NYS (ORPS), the Office of State Comptroller (OSC), the International City/County Management Council (ICMA), and the U.S. Census Bureau. In our data set, a balanced panel data with a total of 16,956 observations (942 assessing units for18 years) is used. It should be noted that, from a total of 984 city- and town-level assessing units in NYS, the observations of the cities and towns in Nassau and Tompkins Counties were excluded because, unlike others, their property tax assessment activities are under the control of county-level assessing units. A brief description of the variables and data sources is presented in Table 1.

Table 1.

Variable Specification and Data Source.

	Variables	Definition	Specification	Data source
Dependent variable	Reassessment	Property Tax Reassessment	1 if the municipality conducted revaluation or update, 0 otherwise	ORPS
Diffusion factor	Neighbors	Share of municipalities sharing a border that reassessed	Number of municipalities reassessed / number of municipalities sharing a border	ORPS
Institutional factor	MCE	Government form	Mayor-Council With Elected Assessor Mayor-Council with Appointed Assessor Council-Manager with Appointed Assessor	ICMA, York Town Board (2008)
	MCA
	CMA
	City	Government level	1 if the municipality is city	ORPS
	Program	Coordinated assessment program	1 if the municipality is in the Coordinated assessment program	ORPS
Fiscal factor	TaxRate	Nominal property tax rate	Property tax levy / assessed value	ORPS
	LocalRevenue	Local source revenue share	(Total revenue − State Aid − Federal Aid) / total revenue	OSC
	Imbalance	Expenditure-Revenue	Total expenditure − Total revenue	OSC
	Expenditure	Expenditure growth rate	(Expenditure_t − Expenditure_{t − 1}) / Expenditure_t	OSC
	Residential	Residential property share	Number of residential parcels / total number of parcels	ORPS
Housing market factor	NParcel	Number of parcels	Number of parcels	ORPS
	Urbanized	Share of houses in an urbanized area	Number of houses in a urbanized area / total number of houses	Census
	Old	Share of old houses	Number of houses build before 1940 / total number of houses	Census
	Rent	Share of rental housings	Number of rental houses / total number of houses	Census
	HouseValue	Median House Value	—	Census
	Vacant	Share of vacant houses	Number of vacant houses / total number of houses	Census
Socio-economic factor	MedianIncome	Median Household Income	—	Census, SAIPE
	Education	Share of highly educated population	Number of adults with college or higher education / total number of adults	Census
	Density	Population density	Total population / square miles of area	Census
Assessment quality	COD	Coefficient of dispersion of residential property	Average percentage deviation of individual assessment ratios from the median assessment ratio	ORPS

Note. ORPS = Office of Real Property Tax Service, NYS; MCE = mayor-council governments with elected assessor; ICMA = International City/County Management Council; MCA = mayor-council governments with appointed assessor; CMA = council-manager governments with appointed assessor; OSC = Office of State Comptroller, NYS; SAIPE = Small Area Income and Poverty Estimates; COD = coefficient of dispersion of residential property; NYS = New York State.

Dependent Variable

The dependent variable indicates the occurrence of property tax reassessment (Reassessment) in a given year. We were able to use the ORPS database, which indicates whether or not the municipalities conducted a city- or townwide revaluation process by which all real property parcels within the municipality are reassessed and updated to reflect market values in a specific year. Given this, the Reassessment variable in our estimation model was dichotomized: a “1” was recorded if the municipality conducted reassessment in a given year, and a “0” was recorded if the municipality used previous years’ property value information to impose the property tax amount.

Both Tables 2 and 3 provide brief descriptive statistics of the frequency (cycle) of property tax reassessment activities across municipalities in NYS over the period 1993-2010: 175 of the 942 units (18.5%) were never reassessed during the time frame of the study; 103 of the total municipalities (10.9%) were reassessed more than 10 times during the 18 years. The number of municipalities that were reassessed in a given year more than tripled for the period 1993 to 2010, indicating a steady increase in the reassessment frequency in upstate New York. This may have resulted from the state’s explicit efforts to induce municipalities to conduct a reassessment on a regular basis.

Table 2.

Reassessment Frequency for the Period 1993 to 2010.

Reassessment frequency	Number of municipalities
Never	175 (18.5%)
1-5 times	451 (47.8%)
6-10 times	213 (22.6%)
11-16 times	103 (10.9)
Total	942

Table 3.

Reassessment Activity for the Period 1993 to 2010.

Year	Number of municipalities which conduced reassessment
1993	109
1996	120
1999	91
2002	297
2005	303
2008	307
2010	360
Total number of municipalities	942

Explanatory Variables

For the key explanatory variables, we constructed two different measures of the local innovation—the regional diffusion factor and the internally established institutional factor. First, to explain the influence of regional diffusion on local innovation, the share of neighboring municipalities adopting reassessment was included in the model (Neighbors). This diffusion factor was constructed by dividing the number of neighboring municipalities reassessed in the previous year by the total number of municipalities sharing a border. The municipalities with a higher share of neighboring cities or towns reassessed are expected to face higher pressure to adopt reassessment. Second, the types of governance structure (political institutions) were included as an institutional factor. They were determined by two dimensions—(a) general government form (mayor-council vs. council-manager governments) and (b) the manner of property assessor selection (elected vs. appointed assessors). In NYS, there are primarily two government forms: mayor-council and council-manager governments. Approximately 80% of cities have the mayor-council form (49 of the 62 cities in 2009), which is higher than the national average. This is partly because cities in NYS are relatively old and have a heterogeneous population composition, and so tend to adopt the mayor-council form, especially with a strong mayor (NYS Department of State, 1996). For towns, the mayor-council government has been a traditional and primary government form in NYS. In response to the growing demands for administrative expertise and political detachment in executive functions, some towns started to adopt the council-manager form; however, the overall number is still very small.¹⁷ In addition, for the manner of assessor selection, as previously noted, more than 80% of NYS’s municipalities currently employ a sole appointed assessor. It is interesting to note that all municipalities adopting the council-manager form have appointed assessor systems only. Thus, we classified the governance structure of cities/towns into three types—(a) mayor-council governments with elected assessor (MCE), (b) mayor-council governments with appointed assessor (MCA), and (c) council-manager governments with appointed assessor (CMA)—assuming that political influence resulting from the election process becomes weaker in the presented order.¹⁸

In addition to such governance structure variables, we added a municipal-level variable (City), indicating whether municipalities in our data set are classified as cities or towns. This variable was coded “1,” if the municipality is a city; or coded “0,” if it is a town. Cities and towns are generally considered general-purpose local government entities with similar powers and administrative functions under the county system. However, although cities are relatively larger in size and have a separate and strong executive branch, towns tend to exercise both legislative and executive functions through the discretionary authority conferred on the town board (NYS Department of State, 2009). When it comes to local government financing, cities tend to not only have a higher property tax rate because most public services including fire and water/sewage are covered by property tax levy but also receive more state aid compared with equivalent towns.¹⁹ Despite the recently growing heterogeneity of sizes and structures in cities and towns, which has led to the blurred distinction between the two, they are still different in their operating systems and some other features.

As discussed earlier, NYS is one of the states in which municipalities have a wide range of autonomy in their property tax assessment administration and practices. However, since the late 1990s, NYS has made extensive efforts to improve municipalities’ assessment quality, including the provision of state aid for achieving more frequent and regular property tax reassessment and enhancing interjurisdictional collaboration. We therefore hold the view that such factors could be intertwined with the regional diffusion factor. In other words, we posit that a state’s influence based on financial incentives (positive inducements per se as one of the coercive isomorphism forces) and administrative coordination toward frequent reassessment of property tax should be explained and controlled in the model. The analysis thus included the Program variable, which indicates whether or not a municipality participated in a coordinated assessment program in a given year.

In support of previous studies of policy adoptions (e.g., Berry & Berry, 1990, 1992; Jensen, 2003) and property tax assessment (e.g., Allen & Dare, 2002; Bowman & Mikesell, 1978; Eom, 2006, 2008; Wassmer, 1993), this study also included several social or economic variables relevant to property tax reassessment activities. Specifically, we considered fiscal, housing market, socioeconomic, and assessment quality factors.

As a fiscal factor, the nominal tax rate (TaxRate), which is calculated as the total property tax levy divided by the total taxable assessed value of all property in the municipality, was included. In practice, a higher level of nominal tax rate is expected to induce stronger resistance of residents against reassessment, because it is more likely to result in an increase in actual tax payments (Eom, 2008). Another variable included as a fiscal factor was the share of local-source revenue in the total revenues (LocalRevenue). The share of local-source revenue represents the level of municipalities’ revenue independence, measured by the ratio of local base revenue to total revenue. In addition, the fiscal stress resulting from fund imbalance or rapid expenditure growth may put more pressure on local officials to do reassessment (without raising a tax rate), thereby incentivizing more frequent reassessments. To control for the fiscal stress that a municipality may face, the variable of fund imbalance (Imbalance, the difference between total expenditure and revenue) and the variable of yearly expenditure growth rate (Expenditure) were included in the model. The last fiscal factor was the share of residential property (Residential), indicating the ratio of total residential parcels to total parcel counts. These variables are expected to be directly associated with the occurrence of property tax reassessment in a given year.

For the housing market factor, the total number of parcels (NParcel) was included to capture the size of the market. In addition, the share of houses in an urbanized area, the proportion of old houses, rental housing, and vacant houses (Urbanized, Old, Rent, and Vacant, respectively) were considered to address the characteristics of the local housing market, along with median house value (HouseValue). It should be noted that these variables were drawn from the U.S. Census Bureau.

To account for the municipalities’ socioeconomic profiles, the following factors were included: median household income (MedianIncome), share of population with college or higher education (Education), and population density measured by total population divided by square miles of area (Density). Education was from the U.S. Census Bureau, and MedianIncome was obtained from the Small Area Income and Poverty Estimates (SAIPE).

Finally, the assessment quality (uniformity) of the property was also considered as a control variable. It was measured by the coefficient of dispersion of residential property (COD).²⁰ As a widely used indicator showing municipalities’ property tax assessment uniformity, COD represents the average percentage deviation of individual assessment ratios from the median assessment ratio (Eom, 2008). Consistent with prior research (e.g., Bowman & Mikesell, 1978; Chicoine & Giertz, 1988), we used the natural logarithm of the COD in our model. The descriptive statistics of all variables included in this analysis are presented in Table 4.

Table 4.

Descriptive Statistics of All Variables.

	Total				1993(2)	2010(9)^a
Variables	M	SD	Minimum	Maximum	M	M
Number of observations	16,956				942	942
Reassessment	0.240	0.427	0	1	0.115	0.382
Neighbors	0.108	0.177	0	1	0.098	0.072
MCE	0.155	0.362	0	1	0.193	0.123
MCA	0.823	0.380	0	1	0.784	0.818
CMA	0.020	0.142	0	1	0.022	0.021
City^b	0.058	0.234	0	1
Program	0.077	0.267	0	1	0	0.154
TaxRate	0.019	0.039	0	0.356	0.031	0.018
LocalRevenue	0.846	0.092	0.109	1	0.854	0.849
Imbalance	−49,802	2,751,046	−8,110,000	8,950,000	57,988	78,650
Expenditure	−0.014	0.348	−.988	7.750	0.039	0.097
Residential	0.628	0.811	0.003	88.59	0.614	0.616
NParcel	4,030.28	9,169.11	157	183,894	3,680.27	4,016.68
Urbanized	0.187	0.257	0	1	0.148	0.159
Old	0.425	0.554	0.024	0.625	0.312	0.401
Rent	0.241	0.568	0.021	0.852	208	0.211
HouseValue^b	93,332	64,814	34,400	708,000	78,413	173,610
Vacant	0.189	0.170	0	0.887	0.188	0.184
MedianIncome	38,824.15	12,954.63	8,298	18,843	32,744.74	40,598.87
Education	0.118	0.042	0.056	0.481	0.114	0.129
Density	468.79	1,326.43	0.533	17,130.48	472.20	466.47
COD	11.839	9.028	0	76.4	16.44	13.55

Note. MCE = mayor-council governments with elected assessor; MCA = mayor-council governments with appointed assessor; CMA = council-manager governments with appointed assessor; COD = coefficient of dispersion of residential property.

Reassessment information from 1993 to 2010 with 1-year lagged information for other variables (1992-2009).

HouseValue and MedianIncome are in 2000 U.S. real dollars.

Estimation Method

Given the dichotomous nature of the dependent variable, we utilized event history analysis (EHA) techniques to test the main hypotheses. Specifically, the estimation process of this study was performed using the Cox regression estimation method.²¹ This statistical technique enables researchers to estimate the impact of time-constant as well as time-varying factors of interest on the probability of the occurrence of property tax reassessment. The highest occurrence rate of the events (here, property tax reassessment) would be once a year, and it is also likely that cities and towns conducted property tax reassessments multiple times during the time period covered by this analysis (18 years). To incorporate this nature of reassessment events, we used the multiple-failure model with discrete time frame (each year). Unlike the standard policy innovation model of Berry and Berry (1990), in which the event (failure) can happen only once, the multiple-failure discrete time frame model allows the probability of the event (failure) to be present even after the event has occurred once.

Results

Table 5 shows the estimation results of the Cox regression analysis. Although the first column reports the baseline model, the second and third columns present the estimation model with county dummies and the model that includes not only the dummies but also the COD variable, respectively. First of all, Neighbors, one of the main predictors of the policy adoption, was found to have a positive association with the likelihood that municipalities conduct reassessment activities more frequently. This finding is consistent with the view that governments tend to adopt innovative policies implemented by neighboring governments (Douglas et al., 2015; Füglister, 2012; Graham et al., 2013; Jensen, 2003; Zhang & Yang, 2008).

Table 5.

Cox Regression Estimation Result.

Variables	Baseline	County dummies	County dummies + COD
Neighbors	1.267*** (.055)	0.262*** (.065)	0.110* (.066)
MCA	0.209*** (.051)	0.344*** (.054)	0.272*** (.054)
CMA	0.380*** (.138)	0.490*** (.144)	0.358** (.144)
City	−0.078 (.128)	−0.016 (.142)	−0.073 (.143)
Program	0.248*** (0.048)	0.243*** (.054)	0.121** (0.053)
TaxRate	−3.843*** (.641)	−2.836*** (.659)	0.450 (.648)
LocalRevenue	0.514*** (.185)	0.206 (.191)	0.073 (.190)
Imbalance	0.001 (.001)	0.001 (.001)	0.001 (.001)
Expenditure	0.001 (.001)	0.001 (.001)	0.001 (.001)
Residential	−0.057 (.154)	−0.090 (.196)	−0.112 (.194)
NParcel	0.001 (.001)	−0.001(.001)	0.001 (.001)
Urbanized	−0.340** (.157)	−0.237 (.183)	0.130 (.100)
Old	−0.121 (.085)	0.137 (.100)	−0.135 (.181)
Rent	0.562** (.257)	−0.067 (.298)	−0.180 (.182)
Log (HouseValue)	−0.620*** (.102)	−0.161 (.155)	−0.059 (.165)
Vacant	0.171 (.117)	−0.167 (.143)	−0.072 (.143)
Log (MedianIncome)	0.183 (.176)	−0.141 (.204)	−0.110 (.206)
Education	2.410*** (.404)	1.762*** (.525)	1.305** (.530)
Density	−0.001 (.001)	0.001 (.001)	0.001 (.001)
Log (COD)			−0.047*** (.002)
Number of observations	16,956	16,956	16,956
Number of subjects	942	942	942
Log likelihood	−27,521.75	−26,973.38	−26,769.57

Note. Standard errors are in parentheses. COD = coefficient of dispersion of residential property; MCA = mayor-council governments with appointed assessor; CMA = council-manager governments with appointed assessor.

p < .1. **p < .05. ***p < .01.

It was also found that MCA had a significant positive impact on the likelihood of implementing property tax reassessment. This result indicates that the institutional setting of the mayor-council government form with appointed assessors is more likely to adopt the reassessment in a given year than those of mayor-council governments with elected assessors. Consistent with our expectations, CMA was also found to be significantly and positively associated with the propensity of adoption of reassessment. It is worthwhile to note that the effect of CMA seems to have the highest coefficient (0.380, p < .01) among institutional-related variables. This suggests that municipalities having council-manager governance forms with appointed assessors tend to conduct the reassessment policy most frequently, followed by the mayor-council with appointed assessors. The mayor-council with elected assessors form turned out to be the least frequent assessment conductor. The additional government form variable, City, turned out to be statistically insignificant. The result demonstrates that whether or not a municipality is a city or a town had no impact on the implementation of a property tax reassessment. As predicted, Program was found to have a highly significant and positive impact on the reassessment. This result implies that participation in a coordinated assessment program is likely to lead to a more frequent reassessment by allowing municipalities to share their limited resources with other jurisdictions in property tax administration. In other words, it suggests that top-down go-betweens in the form of positive inducements can play a role in facilitating the local policy diffusion process.

Regarding the effects of fiscal factor variables, the results appear to be mixed. It was observed that although TaxRate had a significant negative effect on the likelihood of adoption, LocalRevenue had a positive effect. This can be explained by the concept that a higher level of nominal tax rate accompanied by greater tax burden is likely to decrease the likelihood of having frequent reassessment of property in the municipalities. It is reasonable to expect that, as a municipality operates independently from state or federal governments in the context of revenue sources, it is more likely for the city or town to conduct reassessments more frequently to adjust its fiscal needs. Somewhat unexpectedly, the variable of Imbalance and Expenditure turned out to be insignificant, indicating that fiscal stress may not be the primary factor for inducing property tax reassessment. In addition, Residential appeared to have no impact on the likelihood of adoption, implying that the share of residential property as a tax base is not a significant predictor of municipalities’ reassessment decisions.

Of the housing market variables, Urbanized and HouseValue turned out to decrease the likelihood of municipalities’ adopting reassessment policies. Since relatively high market-valued house residents, who are located more in urban areas than rural areas, tend to face an increased tax burden as a result of property revaluation, they may resist government innovation efforts in favor of the frequent reassessment. However, it was found that Rent had a positive relationship with the likelihood of adoption, suggesting that in municipalities with more renter-occupied houses property reassessment activities are more likely to occur. This finding might be attributable to the nature of tax incidence with regard to owner-occupied housing, which causes relatively less political resistance from renters who are, on the surface, free of the direct property tax obligation.²²

With regard to the socioeconomic factor variables, we found that only Education was significantly associated with the likelihood of municipalities adopting property reassessment in a positive way. This may suggest that, in municipalities where the proportion of educated residents is higher, the property tax reassessment is less likely to be resisted because those people are believed to be knowledgeable about the rationale of property revaluation administration.

The estimation result in the second column is the model with county dummies. The county dummies were included to capture all countywide common factors within a county. In this model, we found that the impact of four variables (LocalRevenue, Urbanized, Rent, and Housevalue) that were significant in the baseline model became insignificant. This might have been because such dummies, which are supposed to control countywide common factors, further captured a substantial portion of the variations in the city/town level variables used in this model.

In addition, to more thoroughly examine the relationship between COD and the dependent variable, we added the COD variable, along with the county dummies, to our model. As the last column shows, the results of the most important key variables (Neighbors, MCA, and CMA), indicating statistically significant and positive signs on the coefficients, turned out to be the same as the one shown in the previous models (here, the baseline model and the model with county dummies). This could be the most intriguing finding of this study because the effects of the main explanatory variables (Neighbors, MCA, and CMA), are all positive and statistically significant in three models. As expected, our empirical results confirmed that both the regional diffusion factor and internally established institutional factor, which mainly represent external (neighboring) influences and nested governance structures, respectively, are key driving forces in local governments’ reassessment decisions and implementation. Furthermore, we detected that COD was negatively associated with the propensity of adoption of reassessment. It can therefore be deduced that, in cases where municipalities have relatively higher levels of COD, it is more likely to induce a higher disparity in assessed values of similar residential properties accompanied by inequity problems of tax incidence. Such situations can lead to the propensity of strong resistance of taxpayers to the reassessment activities.

Discussion and Conclusion

To explore the dynamics of the diffusion of an innovation at the local level, we chose to focus on the property tax reassessment policy conducted in NYS cities and towns. Through EHAs using balanced panel data during the period of 1993-2010, we empirically tested the relationship between a set of factors inherent in the state-local nexus and the likelihood of implementing frequent property tax reassessment in local governance settings. Unlike most prior empirical studies of policy adoptions, this study has, by adopting a more detailed, broader approach, at least partially answered the call for a better understanding of the roles of different influences—the three different main actors (internal, external, and go-betweens) and additional institutional factors that can promote or hinder a local government in adopting a policy—in the policy diffusion process.

First, in an attempt to conclude that further analysis of Berry and Berry’s (1990, 1992) integrated approach to the innovation is valuable at the local level, we revisited their widely cited policy innovation framework based on internal determinants (e.g., socioeconomic characteristics specific to the government) and an external (regional) diffusion factor (neighboring governments). Consistent with the policy diffusion approach (e.g., Jensen, 2003; Mooney, 2001; Zhang & Yang, 2008), it was found that the regional influence of neighboring jurisdictions plays a significant role in policy adoption and diffusion.

Second, as with recent studies of policy diffusion (e.g., Douglas et al., 2015; Graham et al., 2013), we focused on “go-betweens” (here, top-down go-betweens in particular) as one of the main factors (actors) influencing local policy adoption decisions. In this study, the role of top-down go-betweens was found to be significant in that NYS has been shown to play a role in motivating their localities to conduct frequent reassessments of property. Given this, we speculate that the diffusion phenomenon stemming from the neighboring effect may be partly due to a state’s effort based on positive inducements (state aid) and interjurisdictional administrative coordination (e.g., encouraging municipalities to share assessors or use the same assessment schedule).

Third, given the main rationale underlying new institutionalism based on Williamson’s (1985) public sector transaction cost theory, it is reasonable to assume that governance structures and rules surrounding local governments shape (create) the incentives politicians and bureaucrats face, each of which is different and further entails cost, thereby resulting in different policy decision making. With this in mind, we attempted to go a step further to capture the impact of political institutions on the behaviors of local actors, including elected officials or bureaucrats, in the context of the policy adoption. For the analysis, we carefully incorporated McCabe and Feiock’s (2005) view of nested levels of institutions (rules), which include overriding standards to control specific choices (constitutional-level rules) as well as operational decisions in a specific policy area (substantive rules). This in turn caused us to expand our focus to two-tiered political institutions influencing local actors’ willingness to adopt the property tax reassessment policy, including the different statewide forms of government and the local property tax assessor structure. In accordance with previous studies (e.g., Carr, 2015; Frant, 1996; McCabe & Feiock, 2005; Svara, 1990), we found that municipalities in the council-manager governance form with appointed assessors are more likely to adopt a property reassessment policy than others are, because their decisions are more related to low-powered incentives.

More interestingly, among the results concerning a combination of each nested institution, municipalities with the form of mayor-council governments with appointed assessors also turned out to have a positive impact on local policy adoption. One possible explanation for this is that although local governments are governed under the mayor-council form, property tax reassessment is mainly performed by assessors who work in proximity to citizens and communities in practice. In turn, substantive-level institutions (elected vs. appointed assessors) are highly influential in determining how the property tax is administered and assessed, as opposed to constitutional-level ones. Given this, the findings appear to suggest that cities and towns with appointed assessors, regardless of constitutional-level institutions (traditional vs. reformed government structures), are more likely to adopt a property tax reassessment than those with elected assessors. This is partially in line with previous studies indicating that appointed officials’ behaviors are not based on high-powered incentives accompanied by political opportunism, but rather on low-powered incentives driven by the pursuit of professional management (Frant, 1996; McCabe & Feiock, 2005).

This study has several intriguing implications that merit discussion. First, although this study explicitly recounted the widely cited previous observations regarding a government’s likelihood of policy innovation, unlike prior research, we extended our view to the local level with a large panel data set covering more than 18 years. Because most previous studies tended to focus on higher levels of government (mostly state-, federal-, or nationwide), this study dealt with cities and towns as the unit of analysis instead, and therefore, contributes to the research on the subject. In addition, this study enriches the literature of policy adoption and diffusion by casting additional light on a largely undocumented issue regarding the hierarchy of rules (nested institutions) affecting local policy decisions. Focusing on the two-tiered hierarchical governance structure influencing the probability of a municipality’s adopting property reassessment provided us with a unique opportunity to explore the complex nature of local government policy-making processes. In support of North’s (1990) and McCabe and Feiock’s (2005) view that institutions shape key local actors’ incentives and subsequent behaviors in the context of policy choice, this study sought to unravel the ways of aligning property tax assessors’ political or administrative interests, behaviors, and policy consequences given both constitutional-level and substantive institutional arrangements. As a result, we found some evidence that main local actors (here, elected versus appointed public officials) participating in the policy choice process have different individual incentives and values regarding policy consequences, given specific political institutions and the socioeconomic circumstances faced by them. While appointed executive officials tended to act based on low-powered, bureaucratic incentives, their elected counterparts were more likely to act in response to the preferences of a majority of their constituents (that is, based on high-powered, political incentives) (Clingermayer & Feiock, 2001; Kim & Eom, 2016; McCabe & Feiock, 2005). It is reasonable to believe that our empirical findings reflect real-world conditions and add some potential post hoc justification to confirm the normative statement about council-manager governments and appointed assessors. In this regard, it would seem that focusing on institutional influences may help answer one of the important questions that remain underexplored in the policy diffusion literature: why a policy is differently implemented or diffused across local governments (i.e., why some jurisdictions adopt a policy [innovation] while others do not). This is why it is important to know the nature of institutional arrangements (policy environment) in which local governments are nested, and, further, what this implies for policy adoption and diffusion in a broader sense.²³

Furthermore, the findings presented here suggest an important practical implication. As briefly mentioned earlier, monitoring local properties regularly and assessing them fairly to achieve higher levels of assessment uniformity obviously takes time and resources (e.g., well-trained staff and sufficient funding for the actual inspection-driven valuations). Such activities may also sometimes entail some resistance from taxpayers. In reality, it is undeniable that, to certain groups of residents (mostly the poor), rapidly rising home values and subsequent increases in property taxes might be viewed as differentiated and relatively unfair tax burdens rather than equitable tax incidences (Bowman, 2006; Eom, 2006; Yinger et al., 1988). Their resistance may cause feasible risks vis-à-vis local politics. Although simply adopting (following) a successful policy implemented by neighboring governments (here, having frequent reassessment of property) can be helpful in easing such significant internal political pressure, it would still make local policy makers (especially mayors and elected assessors) more sensitive to respond to voters’ interests in property tax policies.

Nevertheless, it is important to acknowledge that more frequent revaluation or updating of local properties matters to identify and solve inequity problems embedded in real property taxation. This basically echoes Mikesell’s (1980) argument that “reassessment will realign property tax payments among properties . . . [and] increase effective tax rates without normal budget scrutiny” (pp. 23-24). This study revealed that cities and towns with appointed assessors appear to have been more likely to conduct the property tax reassessment activity regularly and frequently for the period 1993-2010, compared with others with elected assessors. Such a result does not necessarily mean that frequently occurring reassessment of property tax leads to improved appraisal uniformity at the local level; rather, municipalities having appointed assessor systems may have more opportunity to adjust the true market value of property in response to the rapidly changing economic cycles and accurately reflect the needs of taxpayers (e.g., fairly imposed tax rates). As noted above, this implies that, unlike their elected counterparts, because appointed assessors are considered more professional and apolitical based on low-powered incentives, they are more willing to proceed with the reassessment policy while maintaining control over internal political threats.

When considered together, it can be reasonably expected that such a governance circumstance will help benefit both citizens and local government agencies in the long term. Therefore, this exploratory research suggests that local government agencies and actors need to pay greater attention to institutional factors (e.g., having appointed assessors) as a way to ensure that financial resources related to property are efficiently and fairly distributed. Our findings, though limited, may be helpful to guide current policy makers of financially low-performing local government agencies who are willing to pursue more innovative policies, without compromising the needs of their communities.

Although this study has provided important insights into the impact of institutional arrangements on policy adoption in municipal governments, its limitations should be noted for future research. First, many other factors that could influence the likelihood of innovation of property tax reassessment remained untested in this study. For example, more than one city or town sharing an assessor and contracting out some assessment services to private firms seems an especially promising topic, given that related data are available. More importantly, aside from internal actors, external actors, and top-down go-betweens affecting a policy innovation, state-level or national-level professional association memberships and networks (i.e., NYS Assessors’ Association, Inc., International Association of Assessing Officers, and International City/County Management Association) may have a significant impact on the likelihood of municipalities’ adopting reassessment policies. Thus, future studies should determine whether this relationship between epistemic go-betweens and the rate of diffusion indeed exists. If this link is verified, deeper discussion of learning as an effective policy diffusion mechanism would be possible. For a more in-depth examination, it would be worth conducting elite interviews with elected and appointed local assessors, and then comparing two different assessor groups’ motivations for conducting property reassessments.

Second, given that each municipality may have a different standard or rule to evaluate each type of property, and that interjurisdictional collaboration efforts have been made with various forms and versions since the late 1990s in NYS, incorporating these factors into our future empirical model would be more meaningful to entirely capture the dynamics pertaining to a local property tax reassessment process. Although this study offers a short account of the interjurisdictional collaboration in property assessment, future research needs to pay attention to such issues for more convincing analysis and arguments. In addition, if we had been able to include data regarding the initial years of property tax reassessment implemented in NYS and its localities, we would have been able to generate more rigorous estimation results. Given this limitation, one logical next step would be to gather more data covering a longer period and find more convincing historical trends of policy diffusion.

Finally, the data were collected in the NYS local government setting only. Admittedly, this limits the generalizability of this study due to the multiple factors that are not captured in this analysis, such as socioeconomic condition (e.g., economic crisis and income inequality), political ideology (party control), election cycles, interest group and media support, and societal and cultural expectations in the governance system. Readers should therefore bear this in mind before generalizing the results as, nationwide, local governments have very different demographic, cultural, and political environments, as well as varying financial capacities and institutions. Future research is thus warranted in different local settings or other levels of government.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially supported by a Start-Up Grant No. M4081744.100 from Nanyang Technological University, Singapore.

Notes

Author Biographies

Tae Ho Eom is a professor in the Department of Public Administration, Yonsei University, Korea. His research interests include local public finance, public budgeting and financial management, and policy making theories.

Hyunhoe Bae is an associate professor in the Department of Public Administration, Yonsei University, Korea. Her research interests include policy analysis and public finance.

Soojin Kim is an assistant professor of the Public Policy and Global Affairs Programme, School of Social Sciences, Nanyang Technological University, Singapore. Her research interests include public budgeting and financial management, contracting out, and institutional arrangements in policy choices.

References

Allen

Dare

(2002). Identifying determinants of horizontal property tax inequity: Evidence from Florida. Journal of Real Estate Research, 24, 153-164.

Bae

Feiock

R. C.

(2004). The flypaper effect revisited: Intergovernmental grants and local governance. International Journal of Public Administration, 27, 577-596.

Berry

F. S.

Berry

W. D.

(1990). State lottery adoptions as policy innovations: An event history analysis. American Political Science Review, 84, 396-415.

Berry

F. S.

Berry

W. D.

(1992). Tax innovation in the states: Capitalizing on political opportunity. American Journal of Political Science, 36, 715-742.

Berry

F. S.

Berry

W. D.

(2007). Innovation and diffusion models in policy research. In Sabatier

P. A.

(Ed.), Theories of the policy process (pp. 169-200). Boulder, CO: Westview.

Bowman

J. H.

(2006). Property tax policy responses to rapidly rising home values: District of Columbia, Maryland, and Virginia. National Tax Journal, 59, 717-733.

Bowman

J. H.

Mikesell

J. L.

(1978). Uniform assessment of property: Returns from institutional remedies. National Tax Journal, 31, 137-152.

Bowman

J. H.

Mikesell

J. L.

(1989). Elected versus appointed assessors and the achievement of assessment uniformity. National Tax Journal, 42, 181-189.

Carr

J. B.

(2015). What have we learned about the performance of council-manager government? A review and synthesis of the research. Public Administration Review, 75, 673-689.

10.

Carr

J. B.

Karuppusamy

(2010). Reassessing the link between city structure and fiscal policy: Is the problem poor measures of governmental structure? The American Review of Public Administration, 40, 209-228.

11.

Chicoine

D. L.

Giertz

F. J.

(1988). Uniformity in a dual assessment system. National Tax Journal, 41, 247-256.

12.

Clingermayer

Feiock

R. C.

(2001). Institutional constraints and policy choice: An exploration of local governance. Albany: State University of New York Press.

13.

DiMaggio

P. J.

Powell

W. W.

(1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147-160.

14.

Douglas

J. W.

Raudla

Hartley

R. E.

(2015). Shifting constellations of actors and their influence on policy diffusion: A study of the diffusion of drug courts. Policy Studies Journal, 43, 484-511.

15.

Eom

T. H.

(2006). Does home rule overrule the state’s role? An analysis of property tax administration in New York State. The Korean Journal of Policy Studies, 20, 43-67.

16.

Eom

T. H.

(2008). A comprehensive model of determinants of property tax assessment quality: Evidence in New York State. Public Budgeting & Finance, 28, 58-81.

17.

Filer

J. E.

Maok

D. L.

Uze

(1988). Why some states adopts lotteries and others don’t. Public Finance Quarterly, 16, 259-283.

18.

Fisher

G. W.

(1996). The worst tax? A history of the property tax in America. Lawrence: University Press of Kansas.

19.

Fisher

R. C.

(2007). State and local public finance (3rd ed.). Mason, OH: Thomson South-Western College.

20.

Frant

(1996). High-powered and low-powered incentives in the public sector. Journal of Public Administration Research and Theory, 6, 365-381.

21.

Frederickson

H. G.

Johnson

G. A.

Wood

C. H.

(2004). The adapted city: Institutional dynamics and structural change. Armonk, NY: M.E. Sharpe.

22.

Füglister

(2012). Where does learning take place? The role of intergovernmental cooperation in policy diffusion. European Journal of Political Research, 51, 316-349.

23.

Garson

G. D.

(2012). Cox regression. Asheboro, NC: Statistical Associates.

24.

Graham

E. R.

Shipan

C. R.

Volden

(2013). The diffusion of policy diffusion research in political science. British Journal of Political Science, 43, 673-701.

25.

Gray

(1973). Innovation in the states: A diffusion study. American Political Science Review, 67, 1174-1185.

26.

Hawkins

C. V.

Feiock

R. C.

(2011). Joint ventures, economic development policy, and the role of local governing institutions. The American Review of Public Administration, 41, 329-347.

27.

Heavey

(1983). Patterns of property tax exploitation produced by infrequent assessment. American Journal of Economics and Sociology, 42, 441-450.

28.

Ingraham

P. W.

(1993). Of pigs in pokes and policy diffusion: Another look at pay-for-performance. Public Administration Review, 53, 348-356.

29.

International Association of Assessing Officers. (2000). Property tax policies and administrative practices in Canada and the United States. Chicago, IL: International Association of Assessing Officers.

30.

Jensen

J. L.

(2003). Policy diffusion through institutional legitimation: State lotteries. Journal of Public Administration Research and Theory, 13, 521-541.

31.

Karch

(2007). Democratic laboratories: Policy diffusion among the American states. Ann Arbor: University of Michigan Press.

32.

Karuppusamy

Carr

J. B.

(2012). Interjurisdictional competition and local public finance: Assessing the modifying effects of institutional incentives and fiscal constraints. Urban Studies, 49, 1549-1569.

33.

Kim

Eom

(2016). A panel data analysis of the impacts of institutional differences on local governments’ budgetary decisions. International Review of Administrative Sciences, 82, 559-579.

34.

Kwon

Berry

F. S.

Feiock

R. C.

(2009). Understanding the adoption and timing of economic development strategies in U.S. cities using innovation and institutional analysis. Journal of Public Administration Research and Theory, 19, 967-988.

35.

Lee

Chang

Berry

F. S.

(2011). Testing the development and diffusion of e-government and e-democracy: A global perspective. Public Administration Review, 71, 444-454.

36.

Lee

R. D.

Jr. Johnson

R. W.

Joyce

P. G.

(2013). Public budgeting systems (9th ed.). Burlington, MA: Jones & Bartlett Learning.

37.

Lineberry

R. L.

Fowler

(1967). Reformism and public policies in American cities. American Political Science Review, 61, 701-716.

38.

Lowery

(1984). Tax equity under conditions of fiscal stress: The case of the property tax. Journal of Federalism, 14, 55-65.

39.

MacDonald

(2008). The impact of government structure on local public expenditures. Public Choice, 136, 457-473.

40.

McCabe

Feiock

R. C.

(2005). Nested levels of institutions: State rules and city property taxes. Urban Affairs Review, 40, 634-654.

41.

McClelland

(1965). Property tax assessment. In Benson

G. C. S.

Benson

McClelland

Thomson

(Eds.), The American property tax: Its history, administration, and economic impact. Claremont, CA: The Institute for Studies in Federalism, Lincoln School of Public Finance, Claremont Men’s College.

42.

McMillen

(2013). The effect of appeals on assessment ratio distributions: Some nonparametric approaches. Real Estate Economics, 41, 165-191.

43.

Mehta

Giertz

(1996). Measuring the performance of the property tax assessment process. National Tax Journal, 49, 73-85.

44.

Melnik

S. V.

Cenedella

D. S.

(2009). Real property taxation and assessment processes: A case for a better model. New York University Journal of Legislation and Public Policy, 12, 259-320.

45.

Meseguer

(2005). Policy learning, policy diffusion, and the making of a new order. Annals of the American Academy of Political and Social Science, 598, 67-82.

46.

Mikesell

J. L.

(1980). Property tax reassessment cycles: Significant for uniformity and effectiveness. Public Finance Quarterly, 8, 23-37.

47.

Mintrom

(1997). Policy entrepreneurs and the diffusion of innovation. American Journal of Political Science, 41, 738-770.

48.

Mohr

L. B.

(1969). Determinants of innovation in organizations. American Political Science Review, 63, 111-126.

49.

Mooney

C. Z.

(2001). Modeling regional effects on state policy diffusion. Political Research Quarterly, 54, 103-124.

50.

Nelson

K. L.

Svara

J. H.

(2012). Form of government still matters: Fostering innovation in U.S. municipal governments. The American Review of Public Administration, 42, 257-281.

51.

Netzer

(1966). Economics of the property tax. Washington, DC: Brookings Institution.

52.

New York State Department of State. (1996). Local government handbook (5th ed.). New York: Author.

53.

New York State Department of State. (2009). Local government handbook (6th ed.). New York: Author.

54.

New York State Assessors’ Association, Inc. (2010). Real property tax reform white paper: A look at the assessment process and tax reform in New York State. Retrieved from http://nyassessor.com/Portals/3/documents/NYSAA%20White%20Paper%202010.pdf

55.

New York State Department of Taxation and Finance. (2014). Reassessments. Retrieved from http://www.tax.ny.gov/pit/property/learn/reassess.htm

56.

New York State Department of Taxation and Finance. (2015). Towns changing from three member boards of elected assessors. Retrieved from https://www.tax.ny.gov/research/property/assess/training/qualcert/threememberbd.htm

57.

New York State Office of Real Property Tax Services. (2010). Assessor elected/appointed/sole elected/county appointed/county elected 1190 assessor positions. Retrieved from http://www.tax.ny.gov/pdf/publications/orpts/training/qualcert/assessor_type.pdf

58.

North

D. C.

(1990). Institutions, institutional change and economic performance. Cambridge UK: Cambridge University Press.

59.

Ostrom

(1990). Governing the commons: The evolution of institutions for collective action. Cambridge, UK: Cambridge University Press.

60.

Plummer

(2014). The effects of property tax protests on the assessment uniformity of residential properties. Real Estate Economics, 42, 900-937.

61.

Propheter

(2016). Managerial experience and organizational performance: A 15-year panel study of local assessors. Public Administration Review, 76, 438-446.

62.

Renzulli

L. A.

Roscigno

V. J.

(2005). Charter school policy, implementation, and diffusion across the United States. Sociology of Education, 78, 344-366.

63.

Rogers

E. M.

(2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

64.

Ross

J. M.

(2012). Interjurisdictional determinants of property assessment regressively. Land Economics, 88, 28-42.

65.

Ross

J. M.

(2013). A socioeconomic analysis of property assessment uniformity: Empirical evidence on the role of policy. Public Budgeting & Finance, 33, 49-75.

66.

Schelling

(1960). The strategy of conflict. Oxford, UK: Oxford University Press.

67.

Svara

J. H.

(1990). Official leadership in the city: Patterns of conflict and cooperation. New York, NY: Oxford University Press.

68.

Svara

J. H.

Watson

D. J.

(2010). More than mayor or manager: Campaigns to change form of government in America’s large cities. Washington, DC: Georgetown University Press.

69.

Walker

J. L.

(1969). The diffusion of innovations among the American states. American Political Science Review, 63, 880-899.

70.

Wassmer

R. W.

(1993). Property taxation, property base, and property value: An empirical test of the “new view.” National Tax Journal, 46, 135-160.

71.

Williamson

O. E.

(1985). The economic institutions of capitalism: Firms, markets, relational contracting. New York, NY: Free Press.

72.

Yinger

Borsch-Supan

Bloom

H. S.

Ladd

H. F.

(1988). Property taxes and house values. New York: New York Academic Press.

73.

Zhang

Feiock

R. C.

(2010). City managers’ policy leadership in council-manager cities. Journal of Public Administration Research and Theory, 20, 461-476.

74.

Zhang

Yang

(2008). What drives charter school diffusion at the local level: Educational needs or political and institutional forces? Policy Studies Journal, 36, 571-591.

75.

Zodrow

G. R.

(2001). Reflections on the new view and the benefit view of the property tax. In Oates

W. E.

(Ed.), Property taxation and local government finance (pp. 79-111). Cambridge, MA: Lincoln Institute of Land Policy.