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Mundane cash management policies in the American states: a preliminary assessment using the political economy model.


A political economy model, incorporated curved and interactive terms, is used to explain levels of five dimensions of cash management policies in the American states. Results point to a predominant role for economics, political culture, and interest groups as the explanation for policy levels. Further, the explanations are, in many instances, curved and conditional. [C] 2002 Elsevier Science Inc. All rights reserved.

1. Introduction

The political economy model has predicted policy levels in the American states in such diverse areas as welfare, medicaid, and disability policy (Barrilleaux & Miller, 1988; Erickson, Wright, & McIver, 1987; Hanson, 1983; Hwang & Gray, 1991; Wright, Erickson, & McIver, 1987), education policy (Hwang & Gray, 1991), abortion (Meier & McFarland, 1992), environmental regulation (Ringquist, 1993), economic development (Brierly & Feiock, 1993), consumer protection (Meier, 1987a), public utility, insurance, and banking regulation (Skalaban, 1992, 1993), tax policy (Hansen, 1990; Johnson & Meier, 1990), the death penalty (Nice, 1992), and drug abuse policy (Meier, 1992). However, policy areas studied in the cited literature either engendered controversy or periodically experienced some crisis event which caused the issue to percolate to the top of the policy agenda. Under these conditions, the model worked: developed economic and political forces, existing bureaucratic structure, and the presence of well-organized in terest/advocacy groups combined to, one degree or another, explain public policy. But what about policy areas which, by comparison, are comparatively mundane, banal, or everyday in nature? Can the political economy model explain policy levels in these areas as well?

Mundane means, for purposes of this research, that the policy domain operates in an environment relatively free from crisis or controversy. A policy area is therefore classified as mundane only by comparison to other policy areas (Allen, 1999). Cash management policies are one such area. State governments have adopted a broad range of policies which govern such items as allowable state investments and banking relations/investment practices--to name but a few. Nestled with these dimensions are a host of individualized policies--such as policies governing investment of U.S. Treasury obligations, competitive bidding practices on deposits and compensatory balances, account reconciliations services and state authority to invest in Eurodollars. These items do not attract high levels of public scrutiny or agenda attention. Nor does it seem plausible to conceptualize the studied domain in terms of crisis events which periodically cause other policy debates to percolate to the top of the policy agenda. For example, a variety of forces periodically push welfare and education policy, environmental regulations, and taxes to the forefront of the American political consciousness (Hansen, 1990; Hwang & Gray, 1991; Lowery, 1987; Ringquist, 1993; Sigelman, Lowery, & Smith, 1983). By comparison, accounting for and processing funds between collection and expenditure appears to slide within the ground clutter of the public's political radar scope.

2. Measuring cash management policies

Cash management policies refer to procedures adopted by state governments to monitor cash-on-hand between collection of tax revenues and their corresponding expenditure for public purposes. Dichotomous data in the Book of the States, 1996-1997 (Council of State Governments, 1997) allowed for isolation of five policy dimensions. The Guttman scales created to measure the dimensions are defined in Table 1, along with the individual items collected in each scale. (1) High scores on each scale represent high levels of policy.

Table 2 lists state Guttman scale scores according to allowable state investments. High scores reflect high levels of public policy. Standardized scores, used as the dependent measure, provide a comparison across dimensions. Descriptive statistics indicate that all scales are unidimensional, conform to relatively normal univariate distributions, reflect sufficient variation to allow for analysis, are generally uncorrelated, and adequately discriminate among cases, although--as expected given the ratio of cases to items--ties are present.

3. The model: concepts, measurement and hypotheses

The political economy model maintains that policy levels are a function of the economic environment, which constrains all civic activity in American states, the behavior of political institutions, which is constrained by attitudinal pre-dispositions of the polity, and the activities of bureaucratic entities and interest groups.

3.1. Economics

Economics' role with regard to predicting policy is well known (Barrilleaux & Miller, 1988; Brierly & Feiock, 1993; Hansen, 1990; Hwang & Gray, 1991; Williams & Matheny, 1984).

And given that the dimensions of the policy under study all reflect an economic aspect (i.e., money) a relatively substantial association should exist between this component of the model and the policy dimensions. Three measures reflect the economic component of the model (general economic complexity, tax revenue pressure, and social class). Positive relationships are expected between all economic measures and the cash management policy dimensions.

A general economic complexity factor, based on 1990 U.S. Census data, was constructed using total population, population density, and the number of manufacturing establishments and manufacturing employees in a state. A larger population generates more absolute tax revenues which require a broad array of cash management policies. Population density, an urbanism surrogate, is included because high population concentrations indicate a high concentration of taxpayers--and the returns from such areas would require more complex cash management procedures. The industrialization measures reflect the long standing practice of including similar variables in this type of research and are also included because industrialized societies produce a variety of tax revenue streams which necessitate complex cash management stratagems on the part of government. The four variables, subjected to principal components factor analysis, yielded a unidimensional general economic complexity scale. (2) High positive scores reflect highly and densely populated industrialized states.

Tax pressure is important with regard to cash management. The force of tax revenue streams could drive states to adopt more policies to keep track of and manage cash-on-hand between time of collection and expenditure. Six different tax revenues in millions of dollars, subjected to principal components factor analysis using a varimax rotation, resulted in two scales reflecting tax pressure. The first dimension reflects revenue from sales/licensing taxes. The second dimension collected revenues from individual/corporate income taxes. (3) High positive scale scores represent high levels of tax pressure.

Social class, another relevant economic determinants measure, indicates that states with wealthier, more educated citizens would possibly encourage a well regulated cash management system. The social class measure, consisting of traditional indicators of income (median family income and per capita income) and education (percent of college graduate in the population and percentage of the population 18-24 years of age in college) were combined into a unidimensional social class scale through principal components factor analysis. (4) High positive scores represent a financial well-off and well-educated polity.

3.2. Politics

Actions of political institutions are constrained by the forces of public opinion and political culture. In sum, public opinion conditions the range of responses of elected policy makers while political culture limits institutional action by structuring the parameters of acceptable political behavior (Elazar, 1972; Erickson et al., 1987; Wright, Erickson, & McIver, 1985).

Since this article focuses on policy adoption, the central political institution under consideration is the state legislature. A professional legislature, with comparatively better educated members, more resources, and more support staff is, in all likelihood, comparatively better able to navigate its way through the technical requirements of a wide variety of policy issues. Further, such legislatures, one may reasonable surmise, would see a need for regulating the cash management practices inherent in governing state revenue flow. Squire's (1992) professionalization index, which compares state legislatures to the U.S. Congress and assigns a score to each state based upon how closely the state legislature approximates the U.S. Congress, was used in this research. Increasing scores indicate increasing legislative professionalization. (5) A positive relationship is expected between professionalization and level of policy.

In a democratic system, public opinion is presumed to shape the response of political institutions. Two forms of public opinion are partisanship and ideology. Wright et al. (1985) established direct measures for the two aspects of public opinion. The measures, based on aggregated polling data, reflect the party affiliation and liberal/conservative bias of a state's polity. Because Republicans and conservatives are posited as being fiscally conservative and distrustful of bureaucratic schemes, and because high scores on the indices reflect Republican partisanship and a conservative ideology, a negative relationship is expected between these measures and rates of policy adoption.

American political culture is defined as a subset of beliefs, values and styles of action derived from the general culture which constrain state political structures, political behavior and modes of political action (Elazar, 1972, pp. 79-80). Three predominant cultures have been identified in the United States: the individualistic, the moralistic and the traditionalistic. Of the three dimensions, the individualistic and moralistic capture our attention. Substantial segments of the American polity operate within the confines of one or the other of these cultures (Elazar, 1972, p. 96). The individualistic culture, among other characteristic phenomena, will not initiate new policies unless demanded by public opinion (Elazar, 1972, p. 100). On the other hand, the moralistic culture will initiate new policies without any public pressure if it believes the policy will be in the public interest (Elazar, 1972, p. 100). The five dimensions of cash management policies present an unusual test case. None of the policy di mensions incur either a high level of public scrutiny or are accompanied by a high level of public demand. Therefore, as a simple exploratory hypothesis this research posits a negative relationship between the individualistic culture--which does not initiate new policies without a demand by public opinion--and policy levels; and, a positive relationship between the moralistic culture--which will adopt new policies in the absence of public demand if believed to be in the public interest--and policy levels. Johnson's (1976) moralistic and individualistic political culture indices are used in this research. (6) High scores on the indices reflect higher levels of these cultural parameters.

3.3. Bureaucracy

Bureaucratic agencies participate in policy formulation/adoption by using their political support, expertise, vitality, and leadership skills to lobby legislators (Meier, 1987a, 1987b; Meier & McFarland, 1992; Rourke, 1984). The state Treasurer's Office would be the key bureaucratic player in the cash management policy domain. The Treasurer's Office, besides being tasked by law with fiscal management responsibilities, would also understand the utility of the various policies necessary to manage cash between collection and expenditure; and, would also, by definition, have a solid understanding of the technical issues involved in this policy domain. As such, the state's chief financial officer would be a natural source of support for various policies governing cash management practices. A six item unidimensional Guttman scale ([C.sub.R] = .94, [C.sub.S.] = .82), using dichotomous items from the Book of the States, 1996-97, was created to represent the bureaucracy measure. The items measure the following respons ibilities of the Treasurer's Office: investment of excess funds, bond issues, management of debt service, management of bonded debt, arbitrage rebate, investment of retirement and/or trust funds, and deferred compensation. High scores indicate a Treasurer's Office with a wide range of cash management authority. A positive relationship is expected between this scale and the dimensions of cash management policies.

3.4. Interest group activity

Interest groups affect the policy activities of governors (Hansen, 1990; Beyle, 1990), state legislators (Kim & Gray, 1993), state administrators (Abney & Lauth, 1983) and, the general policy process (Barrilleaux & Miller, 1988, Johnson & Meier, 1990; Meier, 1978a; 1988; Meier & McFarland, 1992; Ringquist, 1993). Banking interests constitute the group most likely concerned with the cash management policy domain. The policy dimension governing demand deposits directly affects which banks get what and when. The state investment and banking relations dimension also affect how these interests do business with state governments. Finally, review and oversight dimensions of cash management policies also structure interest group relations with government. The banking interest measure consists of a principal components factor analysis of four measures of financial institutions with a state. High positive factor scores reflect a higher level of banking interests. (7) Because the policies adopted under each dimension pl ace a burden on banking interests, a negative relationship between the size of the banking interests measure and policy levels is expected.

4. Sample, analysis technique and results

4.1. Sample and analysis technique

Analysis results were generated on the 48 contiguous states. Alaska and Hawaii were deleted because of missing data on the public opinion and political culture variables. Multiple regression, incorporating curved and interactive terms, constructed from the pool of included variables, was used to analyze the data. Curved and interactive terms, added one at a time to each equation, were retained if they were statistically significant at the p < .05 level and if they increased the goodness-of-fit criterion in statistically significant fashion (p < .05) (Aiken & West, 1991). (8) The usual rule when using multiple regression is to allow an absolute minimum variable/case ratio of 1:5 (Tabachnick & Farrell, 1989, pp. 128-129). This research includes a pool of 11 independent variables, resulting in a variables to cases ratio of 1:4.36. The inclusion of a single interactive term would result in a smaller ratio. To solve this problem equations were reduced using Achen technique (1982, p. 65). (9) Only the reduced equat ions are reported.

4.2. Results

Eq. (1) in Table 3, which deals with allowable state investments, explains 21% of the variance in this dimension. This equation indicates that social class increases while banking interests, Republican partisanship, and the Treasurers Office decrease the number of policies adopted by any given state. A wealthier, better educated polity generates more cash-on-hand which can be made to earn additional income. Thus, a broader range of state investment policies is understandable. Conversely, banking interests oppose a large number of these policies because they allow states to direct surplus cash away from local depositories. Further, possibly Republican fiscal conservatism does not trust a state government to invest surplus cash-on-hand wisely; thus, Republican dominated states have a narrower range of investment opportunities. Finally, a strong Treasurer's Office minimizes the adoption rate of policies in the area of allowable investments. This finding may be tied to the construction of the Treasurer's Office measure. Three items included in this scale deal with responsibilities for investment of excess funds, bond issues, and investment of retirement and/or trust funds. Possibly a Treasurer's Offi ce, which is responsible for the state's investment practices, keeps a tight rein on the scope of these investments in order to protect the state's supply of excess cash-on-hand.

Eq. (1) also includes curved and interactive terms. The coefficients for the sales/licensing tax pressure terms indicate a classic "U" shaped curve, that is, at the lowest level of tax pressure the scarcity of cash-on-hand may lead to attempts by the state to find additional income through a broad range of investment practices. However, at the midrange of tax pressure, policy levels decrease sharply indicating a lower need to invest surplus cash-on-hand. Finally, when tax pressure is high, there is sufficient cash-on-hand. Under these conditions, a small increase in levels of policy takes place because high tax pressure states need to place their surplus cash somewhere, and they apparently choose safe investment strategies.

The interactive term which combines general economic complexity and the individualistic culture indicates that at the lowest level of an individualistic culture an increase in the level of adopted policy will occur. The moderating effect of the individualistic culture is understandable--an individualistic culture does not initiate new programs unless demanded by public opinion. The absence of this cultural ethos allows an economically complex state to adopt a plethora of policies governing state investment practices.

Eq. (2) on Table 3 deals with banking regulations/investment practices and explains 37% of the variance in policy levels governing banking in relations and investment practices. Results indicate that states with a wealthier, more educated policy have a higher level of banking relations and investment practices. However, contrary to the original hypothesis, a moralistic culture decrease the level of policy within the cash management dimension. This finding may be tied to the ordering of items on this policy scale. Low scale values indicate a state which relies solely on state agencies to review banking and investment practices. The moralistic culture views bureaucracy (state agencies) as bringing desirable politically neutral values to the state's business (Elazar, 1972, p. 100). As a consequence, the moralistic culture evidences, a low policy level because the policies provide for "bureaucratic" oversight of banking relations and investment practices.

This equation also includes interactive and curved terms. The conditional relationship, based on the two measures of tax pressure, indicates that under conditions of higher tax pressure the level of banking relations/investment practice policy evidences a marginal increase beyond what would be anticipated under normal conditions. Higher tax pressure means more funds to be managed--and as a consequence, states move to a complex review process to govern banking and investment practices.

The curved term indicates that where banking interests are weak there is a high level of policy--and review of banking relations/investment practices is carried out by in-house state agencies and outside firms. However, the level of policy falls rapidly as banking interests increase in strength. This fits within the confines of interest group theory. Yet, the shape of the curve changes at the highest level of banking interest strength and a slight increase in the level of policy is noted. Possibly, in states with powerful banking interests, the interests have "captured" the process to such a degree that they are dictating how in-house agencies and outside firms engage in the review of banking relations and investment practices.

Eq. (3), which deals with cash management services, explains 42% of the variance in this dimension. Social class increases while a conservative ideology and strong banking interests decrease the number of cash management policies. A conservative ideology, with its abhorrence of highly complex bureaucratic schemes, would probably oppose highly structure bureaucratic schemes for managing such simple matters as account reconciliation services and the like. Banking interests would be opposed to the high number of policies in this area because complex schemes would significantly raise the cost of providing these relatively simple services.

The interactive term, which combines personal/corporate tax pressure and a moralistic culture, marginally reduces the level of cash management policies. The negative slope may be a function of policy scale construction. Lower scores on the scale reflect "in-house" services--and the moralistic culture's preference for government based bureaucratic services may offset tax pressure.

The curved relationship between personal/corporate tax pressure and policy level indicates that when personal/corporate tax pressure is both high and low policy levels are also low. However, within the midrange of tax pressure policy levels are high. Low tax pressure does not generate sufficient surplus cash-on-hand to justify a complex set of policies. High tax pressure generates such a large cash-on-hand surplus that a complex series of policies for these relatively simple services are deemed irrelevant. It is only at the moderate ranges of tax pressure that states can justify complex policy arrangements for these rather simple services.

Eq. (4), which focuses on the number of policies governing selection of state depositories, explains 49% of the variance. Results indicate that social class increases while personal/corporate tax pressure, a conservative ideological ethos and banking interests decrease the number of policies within this dimension. A state with a wealthier more educated policy would generate more revenue requiring a broader number of state depositories. On the other hand, states with large amounts of cash coming in from personal/corporate income tax apparently need relatively simple arrangements to select which banks to use as depositories. Additionally, states with a conservative ideological oppose high levels of state regulation, and the policies within these dimensions reflect highly bureaucratized regulation. Banking interests would have to deal with the complexities of these policies when trying to qualify as state depositories; therefore, powerful banking interests would oppose a broad range of policies within this dimen sion.

The interactive ideology/moralistic culture term indicates that culture moderates the relationship between ideology and policy level. Whereas states with a conservative bias minimize policy on this dimension, in the presence of a moralistic culture policy levels are increased. The moralistic cultural ethos--with its concern for the public good and its trust in bureaucratic arrangements--requires a minimal level of safeguards when it comes to choosing depositories for the public wealth.

The final set of terms in this equation require a complex explanation. First, sales and licensing tax pressure is related in curvilinear fashion to the level of policy governing depository selection. However, the sales/licensing tax pressure measure is also part of an interactive term which includes the moralistic culture. Given that the tax revenue measure is a joint feature of both the curved and interactive expressions, this set of expressions should be discussed in interrelated fashion (Aiken & West, 1992, p. 69).

The magnitude and direction of the first order tax pressure term and the negative slope of its curved counterpart indicate that the relationship is defined by an inverted U-shaped curve. At both low and high levels of tax pressure policy levels are low while at midranges of tax pressure rates policy levels increase. The interactive term indicates that the relationship between a moralistic culture and policy level is moderated by the rate of tax pressure. Apparently the high level of surplus cash-on-hand moderates the usual demand of the moralistic culture for adoption of a large number of bureaucratic policies.

The final equation in Table 3 deals with protecting demand deposits and indicates that the model explains 53% of the variance. Increases in state economic complexity and social class lead to a complex array of policies to protect the state's demand deposits. On the other hand, Republican partisanship, a conservative ideological bias and strong banking interests decrease the number of adopted cash management policies. Republican and conservative antipathy to increased regulation extends even to policies dealing with mundane aspects of fiscal management. Further, we would expect banking interest opposition in this area because this sector would incur higher costs for doing business with the state.

A complex finding is evident for this equation. The negative slopes of first order and curved expressions of the tax pressure terms indicate a predominantly negative concave relationship between tax pressure and the level of policy. At low levels of tax pressure policy levels are high. Possibly the scarcity of surplus cash-on-hand drives these states to want more safeguards for the relatively limited amount of cash they have to deposit. As the level of tax pressure increases toward the midrange, policy levels undergo a shallow decrease, until at high tax pressure levels a precipitous drop in policy levels is evident. Apparently, as cash-on-hand becomes plentiful, less is required in the way of safeguards for demand accounts--or, put another way, cash-on-hand is so plentiful that high levels of safeguards are not considered a high priority. Political culture plays a role in this system as well; moderating the relationship between tax pressure and policy levels. When tax pressure is low, high rates of policy ad option caused by the scarcity of cash are marginally increased; possibly because the moralistic ethos is interested in enhancing the public good and because this cultural ethos views bureaucratic regulation positively.

5. Conclusions

Several conclusions derive from the analysis. First, the four component political economy model's overall utility varied across policy dimensions. The best results were evident for the policy dimensions which subsumed protecting demand deposits and selecting depositories. In these instances 53 and 49% of the variance was explained, respectively. The worst results were evident for adoption rates of policies dealing with allowable state investments, where only 21% of the variance was explained. Between these extremes, the model explained between 37 and 42% of the variance in policies governing complexity of cash management services and banking relations/investment practices, respectively. The range of results for the five policy dimensions indicates that additional research is needed in order to adequately explain cash management policy levels. One possible approach might be to question whether the adoption of "mundane" policies is simply a function of internal state characteristics--as studied here--or whether , as some suggest (Berry & Berry, 1990; Berry, 1994; Hayes, 1996; Mintrom, 1997; Mintrom & Vergari, 1996, 1998), policies diffuse through states, with more states taking action as they observe the experience of other states.

A second major conclusion focuses on the economic component of the model. As anticipated, economic measures played a major role in explaining all five dimensions of cash management policy. This result was anticipated because the policy dimensions deal with cash management and economically complex states with high tax pressure and wealthier, more educated polities were expected to generate large amounts of cash that would require special handling between time of collection and expenditure. However, what was not expected was the complexity of the relationships between economic considerations and policy levels. For example, while the relationship between social class and all policy dimensions does conform to a straightforward linear relationship, the tax pressure measures reflect either curved or conditional relationships and the economic complexity measure combines with various aspects of political culture. These terms were included in ad hoc fashion with post hoc explanations created to explain the relationshi ps. Thus, these economic findings need to be replicated in other policy areas in order to determine whether the results are idiosyncratic only to mundane policies or whether they are applicable to a broad range of policies.

A similar statement can be made about the political culture dimension of the model. A moralistic culture directly influenced policies affecting banking/investment practices and protection of demand deposits and moderates the effect of economic considerations on two other policy dimensions: complexity of cash management services; and, methods of selecting depositories. A similar conditional relationship was evident for the individualistic ethos in regards to allowable state investments. Once again, the nexus between economics and culture needs to be replicated for other policy areas in order to determine whether this set of findings is idiosyncratic to the special policies studied herein or whether such relationships are present in other areas, as well.

While the overall results indicate that economics and political culture do constitute a consistent--albeit complex--set of explanations for adoption of cash management policies, some aspects of politics are present: partisanship played a role in explaining allowable state investment policies and policies governing protection of demand deposits; and, ideology has a direct and conditional role to play in explaining adoption rates for three policy dimensions: complexity of cash management services, methods of selecting depositories, and protection of demand deposits.

The partisanship, ideology, and political culture measures indicate that politics plays a role in explaining the level of mundane policy adoption. However, a separate measure of politics--legislative professionalism--exerted no effect on any of the policy dimensions. Three alternate explanations may be tied to this outcome. First, the "mundaneness" of the policy area may not require a highly technical response on the part of state legislatures--that is, they may simply be responding to bureaucratic recommendations. As such, legislative response to policy needs may be similar regardless of the nature of legislative professionalism. Second, most professionalism measures tend to combine weighted scores for length of tenure, staff size, session length, and the budget process. The current research scores state legislatures as approximating the structure of the U.S. Congress. Thus, the current findings could be attributed to employment of a different measure. However, there is also a third reason for the consistent ly null finding: quite possibly what is required is a measure of state legislative capacity to process information. A state legislature with a high capacity to process technical information would be better able to profit from the experience of other states.

Another interesting null finding centers on the rather poor performance of the Treasurer Office measure. This concept was only useful in the area of allowable state investments-and the construction of the Treasurer Office measure (which focused mainly on this office's investment control responsibilities) would indicate that this relationship should be anticipated. However, possibly the bureaucracy measure employed in this research needs improvement. For example, an institutionally strong Treasurers Office (as measured here) with a minuscule staff might be incapable of exerting an effect on many of these policy domains--providing a broad field of play for organized interests to restructure policy to meet their own needs; as, indeed, results indicate for the banking interest measure.

The banking interest measure played a role with regard to three policy dimensions: banking and investment practices, methods of selecting depositories, and protection of demand deposits. All three dimensions are intimately related to how banking interest carry out daily tasks. The banking interest relationships might indicate that these organized interests pick and choose among various policy dimensions--concentrating only on dimensions which impact their day-to-day internal operations. This point is deserving of closer scrutiny because it leads to the conclusion--insofar as mundane policies are concerned--that interest groups pay attention to policies that affect their day-to-day operations because that is where increased costs of operation may become most prevalent.
Table 1

Definitions of policy dimensions and scale items used in Guttman scales
to measure the five dimensions of cash management

Scale                                Contents (scale items listed
                                      according to scale position)

Allowable state investments          Definition: State investment
                                     Scale items: U.S. Treasury
                                      obligations, states certificates
                                      of deposit, U.S. agency
                                      obligations, repurchase
                                      agreements, commercial paper,
                                      banker's acceptance, state/local
                                      government obligations, corporate
                                      notes/bonds, time deposits, mutual
                                      funds, national certificates of
                                      deposit, Eurodollar certificates
                                      of deposit or time deposits

Banking relations and investment     Definition: Practices for periodic
 practices                            review of state bank deposits and
                                      state investments in stocks and
                                     Scale items: State agency review of
                                      banking practices, state agency
                                      review of investment practices,
                                      review of investment practices
                                      done within the year, review of
                                      banking practices done within the
                                      year, investment practices
                                      reviewed by outside firm, banking
                                      practices reviewed by an outside

Complexity of cash management        Definition: Safeguards to review
 services                             cash handling services
                                     Scale items: Preparation of cash
                                      management services done by both
                                      in-house agency and outside firm--
                                      and dual control covers: automatic
                                      clearinghouse, account
                                      reconciliation services, wire
                                      transfers, lock boxes, zero
                                      balance accounts

Selection of depository              Definition: Procedures used to
                                      select state depositories
                                     Scale items: Use of competitive
                                      bids, agency convenience,
                                      depositor's convenience,
                                      applications, compensating

Policies protecting demand deposits  Definition: Safeguards for state
                                      accounts maintained in banks
                                     Scale items: Collateralization
                                      above federal insurance level,
                                      fee for service method determines
                                      compensation, competitive bidding
                                      procedure determines compensation,
                                      collateralization in excess of
                                      100% required

Scale                                Data source

Allowable state investments          Book of the States, 1996-97,
                                      pp. 233-234

Banking relations and investment     Book of the States, 1996-97,
 practices                            pp. 235-236

Complexity of cash management        Book of the States, 1996-97,
 services                             pp. 235-236

Selection of depository              Book of the States, 1996-97
                                      pp. 235-236

Policies protecting demand deposits  Book of the States, 1996-97,
                                      pp. 237-238
Table 2

State Guttman scale scores for the five dimensions of cash management
policy, 1996

State                Investments             Banking relations

                     Raw        Z          Raw             Z

Alaska               12.5       1.25       2.5             -1.24
Delaware             12.5       1.25       4.0               .06
Minnesota            12.5       1.25       4.5               .49
Montana              12.5       1.25       4.5               .49
Vermont              12.5       1.25       2.5             -1.24
Nebraska             12.5       1.25       4.0               .06
Oregon               12.0       1.09       5.0               .92
New Jersey           12.0       1.09       6.0              1.79
Wisconsin            12.0       1.09       5.0               .92
Connecticut          11.5        .92       6.0              1.79
Georgia              11.5        .92       5.0               .92
South Dakota         11.5        .92       4.5               .49
Arizona              11.0        .76       3.5              -.37
California           11.0        .76       5.0               .92
Florida              11.0        .76       5.0               .92
Kentucky             11.0        .76       3.5              -.37
Oklahoma             11.0        .76       4.5               .49
Utah                 11.0        .76       2.5             -1.24
Wyoming              11.0        .76       4.5               .49
Louisiana            10.5        .60       2.5             -1.24
New Hampshire        10.5        .60       4.5               .49
Virginia             10.5        .60       5.0               .92
Colorado             10.0        .44       5.0               .92
West Virginia        10.0        .44       2.0             -1.67
Iowa                  9.0        .11       1.0             -2.54
New Mexico            9.0        .11       4.5               .49
New York              9.0        .11       3.5              -.37
Pennsylvania          9.0        .11       6.0              1.79
North Carolina        8.5       -.04       4.5               .49
Nevada                8.0       -.20       4.5               .49
South Carolina        8.0       -.20       3.5              -.37
Idaho                 7.0       -.53       4.5               .49
Texas                 7.0       -.53       2.5             -1.24
Washington            7.0       -.53       3.5              -.37
Tennessee             6.5        -.69      2.5             -1.24
Maine                 6.0        -.85      3.5              -.37
Maryland              6.0        -.85      4.5               .49
Ohio                  6.0        -.85      4.5               .49
Illinois              5.0       -1.18      5.0               .92
Massachusetts         5.0       -1.18      4.5               .49
Michigan              5.0       -1.18      3.5              -.37
Mississippi           5.0       -1.18      4.5               .49
Rhode Island          5.0       -1.18      4.0               .06
Indiana               4.5       -1.34      2.5             -1.24
Alabama               4.0       -1.50      4.5               .49
Arkansas              4.0       -1.50      2.5             -1.24
Hawaii                4.0       -1.50      2.5             -1.24
Kansas                4.0       -1.50      2.0             -1.67
Missouri              4.0       -1.50      4.5               .49
North Dakota          2.5       -1.99      2.5             -1.24

[C.sub.R]/[C.sub.S]    .92/.72    .92/.72   .93/.67          .93/.67
Mean                  8.6       -1.73E-16  3.9             -1.06E-16
S.D.                  3.0        1.00      1.1              1.00
Skewness              -.34       -.34      -.41             -.41
Kurtosis             -1.32      -1.32      -.43             -.43
Variance              9.48       1.00      1.33             1.00

State                Cash management           Select deposit

                     Raw          Z          Raw          Z

Alaska                .0          -.93       4.5           1.57
Delaware              .0          -.93       1.5           -.28
Minnesota            2.0            .5       1.5           -.28
Montana              3.5           .80       1.5           -.28
Vermont              3.5           .80       1.5           -.28
Nebraska             1.5          -.18        .0          -1.21
Oregon               4.0          1.05        .0          -1.21
New Jersey           6.0          2.05       3.0            .64
Wisconsin            2.5           .30       2.5            .33
Connecticut          5.5          1.80       1.5           -.28
Georgia              5.0          1.55        .0          -1.21
South Dakota         2.5           .30       1.0           -.59
Arizona              4.5          1.30       1.5           -.28
California            .0          -.93       5.0           1.88
Florida              5.0          1.55       1.5           -.28
Kentucky              .0          -.93       1.5           -.28
Oklahoma             1.5          -.18       3.0            .64
Utah                 3.5           .80       2.5            .33
Wyoming               .0          -.93       1.0           -.59
Louisiana             .0          -.93       1.5           -.28
New Hampshire        1.5          -.18       4.0           1.26
Virginia             2.5           .30       3.5            .95
Colorado             5.0          1.50       5.5           2.19
West Virginia        1.0          -.43       3.5            .95
Iowa                  .0          -.93       1.5           -.28
New Mexico            .0          -.93       4.0           1.26
New York              .0          -.93       1.0           -.59
Pennsylvania         4.0          1.05        .0          -1.21
North Carolina        .0          -.93       4.0           1.26
Nevada                .0          -.93       1.0           -.59
South Carolina        .0          -.93       5.0           1.88
Idaho                3.0           .55       1.5           -.28
Texas                 .0          -.93        .0          -1.21
Washington            .0          -.93       3.5            .95
Tennessee              .0          -.93       .0          -1.21
Maine                  .0          -.93      5.0           1.88
Maryland              5.5          1.80      1.5           -.28
Ohio                  5.0          1.55       .0          -1.21
Illinois              3.0           .55      1.5           -.28
Massachusetts         4.0          1.05      3.5            .95
Michigan               .0          -.93      3.0            .64
Mississippi           1.5          -.18       .0          -1.21
Rhode Island          4.0          1.05       .0          -1.21
Indiana                .0          -.93       .0          -1.21
Alabama                .0          -.93      3.0            .64
Arkansas               .0          -.93       .0          -1.21
Hawaii                 .0          -.93      1.5           -.28
Kansas                1.5          -.18      2.5            .33
Missouri              2.0           .05      2.5            .33
North Dakota           .0          -.93       .0          -1.21

[C.sub.R]/[C.sub.S]    .90/.65      .90/.65   .91/.72       .91/.72
Mean                  1.8          5.55E-17  1.9           3.03E-17
S.D.                  2.0          1.00      1.6           1.00
Skewness               .55          .55       .48           .48
Kurtosis             -1.15        -1.15      -.73          -.73
Variance              4.03         1.00      4.03          1.00

State                Protect deposits

                     Raw            Z

Alaska               3.0              .39
Delaware              .0            -1.94
Minnesota            4.5             1.57
Montana              2.5              .00
Vermont              4.5             1.57
Nebraska             1.5             -.77
Oregon               2.5              .00
New Jersey           3.5              .78
Wisconsin            2.0             -.38
Connecticut          3.5              .78
Georgia               .0            -1.94
South Dakota         4.5             1.57
Arizona              4.0             1.17
California           1.0            -1.16
Florida              4.5             1.57
Kentucky             3.5              .78
Oklahoma             2.5              .00
Utah                  .0            -1.94
Wyoming              2.5              .00
Louisiana            4.5             1.57
New Hampshire        2.0             -.38
Virginia             2.5              .00
Colorado             3.5              .78
West Virginia        3.5              .78
Iowa                 2.5              .00
New Mexico           3.5              .78
New York             2.0             -.38
Pennsylvania         1.5             -.77
North Carolina       1.5             -.77
Nevada               3.0              .39
South Carolina       1.0            -1.16
Idaho                2.5              .00
Texas                4.0             1.17
Washington           2.5              .00
Tennessee            2.5              .00
Maine                1.5             -.77
Maryland             3.5              .78
Ohio                 2.5              .00
Illinois             2.5              .00
Massachusetts        3.0              .39
Michigan             2.5              .00
Mississippi          4.0             1.17
Rhode Island         1.5             -.77
Indiana               .0            -1.94
Alabama              1.5             -.77
Arkansas             2.5              .00
Hawaii               3.5              .78
Kansas               2.5              .00
Missouri             1.0            -1.16
North Dakota          .0            -1.94

[C.sub.R]/[C.sub.S]   .93/.74         .93/.74
Mean                 2.4             1.55E-16
S.D.                 1.2             1.00
Skewness             -.32            -.32
Kurtosis             -.45            -.45
Variance             1.64            1.00
Variable                     Y1      Y2       Y3    Y4    Y5

Correlations (Pearson's r)
 among the five scales
Y1, state investments       1.00
Y2, banking relations        .27 *  1.00
Y3, cash management          .13     .55 **  1.00
Y4, select depository        .13    -.08     -.14  1.00
Y5, protect deposits         .21     .02      .20  -.01  1.00

* p < .05.

** p < .01.
Table 3

Explaining levels of cash management policies in 48 American states,

Independent variables                Allowable state
                                     investments (Eq. (1))

Constant                             -.17
Sales/licensing tax pressure         -.67 *
Sales/licensing tax
 [pressure.sup.2]                     .24 *
Personal/corporate tax pressure
Personal/corporate tax
Sales/licensing tax x personal/
 corporate tax
General economic complexity           .72
Social class                          .69 **
Legislative professionalism
Public opinion--partisanship         -.55 **
Public opinion--ideology
Moralistic culture                    .35
Personal/corporate tax X moralistic
Sales/licensing tax X moralistic
Ideology X moralistic
Individualistic culture              -.007
Economic complexity X individualist  -.47 *
Treasurers office                    -.43 **
Banking interests                    -.65 *
Banking [interests.sup.2]
Adj-[R.sup.2]                         .21
F-ratio                              2.31 *

Independent variables                Banking and
                                     practices (Eq. (2))

Constant                             -.17
Sales/licensing tax pressure          .39 *
Sales/licensing tax
 [pressure.sup.2]                     .26 *
Personal/corporate tax pressure      -.05
Personal/corporate tax
Sales/licensing tax x personal/
 corporate tax                        .26 **
General economic complexity
Social class                          .70 **
Legislative professionalism
Public opinion--partisanship
Public opinion--ideology
Moralistic culture                   -.48 **
Personal/corporate tax X moralistic
Sales/licensing tax X moralistic
Ideology X moralistic
Individualistic culture
Economic complexity X individualist
Treasurers office
Banking interests                    -.51 *
Banking [interests.sup.2]             .31 *
Adj-[R.sup.2]                         .37
F-ratio                              4.95 **

Independent variables                Cash management
                                     services (Eq. (3))

Constant                              .32
Sales/licensing tax pressure          .14
Sales/licensing tax
Personal/corporate tax pressure      -.52
Personal/corporate tax
 [pressure.sup.2]                    -.37 *
Sales/licensing tax x personal/
 corporate tax
General economic complexity
Social class                          .53 **
Legislative professionalism
Public opinion--partisanship
Public opinion--ideology             -.35 **
Moralistic culture                   -.03
Personal/corporate tax X moralistic  -.49
Sales/licensing tax X moralistic
Ideology X moralistic
Individualistic culture
Economic complexity X individualist
Treasurers office
Banking interests
Banking [interests.sup.2]
Adj-[R.sup.2]                         .42
F-ratio                              5.99 **

Independent variables                Select depository
                                     (Eq. (4))

Constant                              .46 *
Sales/licensing tax pressure         -.69
Sales/licensing tax
 [pressure.sup.2]                    -.37 **
Personal/corporate tax pressure      -.84 **
Personal/corporate tax
Sales/licensing tax x personal/
 corporate tax
General economic complexity           .87
Social class                          .76 **
Legislative professionalism           .35
Public opinion--partisanship         -.23
Public opinion--ideology             -.62 **
Moralistic culture                   -.20
Personal/corporate tax X moralistic
Sales/licensing tax X moralistic     -.45 **
Ideology X moralistic                 .29 *
Individualistic culture              -.25
Economic complexity X individualist
Treasurers office                    -.20
Banking interests                    -.63 **
Banking [interests.sup.2]
Adj-[R.sup.2]                         .49
F-ratio                              4.33 **

Independent variables                Protect demand
                                     deposits (Eq. (5))

Constant                               .82 **
Sales/licensing tax pressure
Sales/licensing tax
Personal/corporate tax pressure      -2.07 **
Personal/corporate tax
 [pressure.sup.2]                     -.76 **
Sales/licensing tax x personal/
 corporate tax
General economic complexity            .61 **
Social class                           .46 **
Legislative professionalism
Public opinion--partisanship          -.85 **
Public opinion--ideology              -.55 **
Moralistic culture                     .37
Personal/corporate tax X moralistic    .29 **
Sales/licensing tax X moralistic
Ideology X moralistic
Individualistic culture
Economic complexity X individualist
Treasurers office
Banking interests                     -.80 **
Banking [interests.sup.2]
Adj-[R.sup.2]                          .53
F-ratio                               7.09 **

Note: Entries are regression coefficients computed on the basis of
centered data. Reported results are for reduced equations only and empty
cells reflect variables eliminated during the reduction process. See
note 9 for an explanation of the reduction process. N of cases for all
equations equals 48--Alaska and Hawaii were deleted because of missing
data of the public opinion and political culture variables.

* p < .05.

** p < .01.


(1.) Guttman scaling, also known as scalogram analysis and cumulative scaling, is a procedure designed to order both items and subjects with respect to some underlying cumulative continuum. The scale score for each case allows accurate prediction of the case's acceptance of each dichotomous item in the scale (McIver & Carmines, 1981, pp. 40-41). For example, a scale score of three indicates a positive response to items 1, 2 and 3 and to none of the other items in the scale. In this research this means that a state would have adopted the first three policies in a scale, but not the remaining policies within the dimension. Use of Guttman scales does limit the inquiry. While scales do represent the cumulative level of policy in each state, nothing can be said about the relatively simplicity/complexity of items within each scale. However, use of the scaling technique is justified. The data exists in dichotomous form and Guttman scaling is an ideal technique to summarize such data. Scale construction conformed to recommended procedures and employed traditional statistics to assess scale reliability: [C.sub.R] = 0.90 and [C.sub.s] = 0.65.

(2.) Factor analysis is a statistical technique whose objective is to represent a set of variables in terms of a smaller number of more abstract scales. The analysis revealed that the four variables represent an underlying continuum labeled "general economic complexity." The technique of factor analysis combined the four variables into a single unidimensional weighted scale and the scale scores were used as the values to represent the concept. See Kim and Mueller (1978) for an explanation of this technique. Log transformations, prior to factor analysis, corrected skewed univariate distributions on all measures. General economic complexity factor loadings: number of manufacturing employees, 1987, 0.98; number of manufacturing establishments, 1987, 0.97; 1990 total population, 0.95; and, 1990 population density, 0.78. The factor explains 96% of the variance, eigenvalue: 3.44.

(3.) Log transformations, prior to factor analysis, corrected skewed univariate distributions on all measures. Factor analysis results are arrayed below:
                                    Sales/licensing  Personal/corporate
Variable                             tax pressure       tax pressure

Log sales tax motor fuel in               .94               .19
 millions, 1994
Log motor vehicle license revenue         .88               .22
 in millions, 1994
Log total license revenue in              .88               .11
 millions, 1994
Log total gross receipts/sales tax        .66              -.03
 revenues in millions, 1994
Log personal income tax revenues          .13               .90
 in millions, 1994
Log corporate tax revenues in             .09               .92
 millions, 1994
Eigenvalue                               2.96              1.78
Percent explained variance              49.4              29.7

(4.) Social Class factor loadings: percent college graduates, 1990, 0.92; percent high school graduates, 1990, 0.92; median household income, 1989, 0.83; per capita income, 1989, 0.68. The factor explains 72% of the variance. Eigenvalue: 2.88.

(5.) Squire's index contains values interpreted as outliers. Scores were recorded to eliminate this problem: New York, 0.659-0.309; Michigan, 0.635-0.308; California, 0.626-0.307; Massachusetts, 0.614-0.306; Pennsylvania, 0.336-0.305; Ohio, 0.329-0.304.

(6.) The moralistic and individualistic indices contain values interpreted as outliers. Scores were recorded to eliminate this problem. Moralistic culture: Utah, 0.93-0.38; Idaho, 0.68-0.37; Kansas, 0.44-0.36; Wyoming, 0.42-0.35; South Dakota, 0.37-0.34. Individualistic culture: Rhode Island, 0.87-0.83; New Mexico, 0.84-0.82.

(7.) Data source: 1994 County and City Databook, Table A, p. 14, columns 194-197. The first two measures in the scale reflect high concentrations of financial institutions and were construct by dividing the number of banking offices and savings and loan offices per state in 1990 by the state's land mass in square miles. These measures were augmented by dividing, the bank and savings and loan deposits per state in 1990 by the number of bank and savings and loan offices in each state as of 1990. Three measures were subjected to log transformations, prior to factor analysis, to correct skewed univariate distributions. Factor loadings: log savings office density, 0.90; log bank office density, 0.89; saving deposits, 0.68; log bank deposits, 0.63. The factor explains 61.9% of variance. Eigenvalue: 2.47.

(8.) Interactive and curved terms are not usually included in an OLS equation unless some a priori theoretical justification exists. In this instance terms were included in a theoretical exploratory fashion and post hoc explanations developed to explain results. Subsequent replication will determine the robustness of the reported findings. The process used to create the equations is complex. First, an exhaustive list of curved and interactive terms was created. All variables which needed to be standardized were subjected to this procedure prior to construction of the curved and interactive terms (Aiken and West, 1991). Second, an 11 variable linear equation was generated using the measures outlined in this article. Third, curved terms were added to the linear equation--one at a time. If a curved term met the statistical criteria for inclusion it was retained. If the term failed to meet the statistical criteria for inclusion it was discarded. Fourth, the same procedure was used to isolate interactive terms for inclusion. Fifth, the pool of retained curved and interactive terms were then added--one at a time--into the linear equation to determine if all relevant terms should be included. Statistically significant increases in [R.sup.2], attributable to the inclusion of the curved and interactive terms, were: Eq. (1), 16%; Eqs. (2) and (3), 11%; Eq. (4), 24%; Eq. (5), 31%.

(9.) Several techniques are available for reducing equations. One technique involves eliminating variables with insignificant bivariate correlations with the dependent variable(s). Another focuses on a mechanical backwards or forwards elimination of variables based on some a priori value of the F-statistic. Both techniques produce problems--the former because it precludes testing for curved and interactive terms and the latter because it produces results that are troublesome and mis-leading. Instead the process recommended by Achen (1982, p. 65) was adopted. Achen's technique requires that independent variables, not included as part of non-linear terms, with t-scores less than 1.40 must be deleted. Deletion is achieved by removing the variable with the smallest t-score below 1.40 and then rerunning the equation. This process is continued until all remaining variables have t-scores at or above the 1.40 threshold. At this point deleted variables are re-entered, one at a time, on a first-out-first-in basis, to d etermine if any excluded variables--upon re-entry--meets the t-score threshold. Using this technique means that some included variables are not statistically significant. Achen's process, far from fool-proof, does allow the researcher more control over which measures are eliminated. This technique did not, in all instances, result in the desired 1:5 ratio: Eq. (1), 1:5.33; Eq. (2), 1:6.85; Eq. (3), 1:6.85; Eq. (4), 1:3.42; Eq. (5), 1:5.33.


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David W. Allen *

* Tel: +1-970-491-5751.

E-mail address: (D.W. Allen).

David W. Allen is an Associate Professor in the Department of Political Science at Colorado State University.
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