THE ACB

COMPUTERIZED

SOCIAL COST BENEFIT ANALYSIS

SYSTEM

I. THE PROBLEM

Whereas the private sector can examine prices and profits to measure the costs and benefits of its actions, the public sector can rarely quantify all significant gains and losses resulting from alternative choices.

Although the theoretical tools to evaluate costs and benefits are well developed, few policymakers, utilize these concepts. The failure to employ cost benefit analysis arises from the expense and time involved in measuring complicated phenomena. Given the heterogeneity of policies, costs, and benefits, governments seeking to comprehensively measure impacts, must typically spend tens of thousands of dollars, and experience delays of months or years.

Policies are thus generally made on the basis of feelings and hunches--while taxpayers and potential beneficiaries suffer the consequences. Politicians usually have no way of knowing the optimal number of police to hire, or how much society should spend on pollution control. Resources are allocated without knowledge of the degree to which additional police reduce the crime rate, and the benefits of such reductions relative to the costs.

In addition, when cost benefit analysis is applied, significant gains and losses are often omitted, even by experts, due to difficulties typically encountered in collecting information. For example, one of the greatest costs of crime--fear--is rarely considered in analyses of criminal justice policy. Furthermore, information from some studies may be overlooked in an age when data expands exponentially. Moreover, policymakers are rarely able to compare the total costs and total benefits arising from different types of expenditure--say spending on roads, on police, or on fire protection, which is a precondition for rationally setting priorities and allocating scarce resources.

The failure to comprehensively measure costs and benefits has also lowered the level of political and policy debates. Participants generally recite only preconceived ideas, general principles, and isolated facts. In addition, each side of any debate cites "studies" in support of their position--creating a cloud of confusion and mistrust in voter's minds. Many of these studies are bought and paid for by the proponents themselves with conclusions determined in advance. No mechanism exists to determine general tendencies from a broad sample of all studies.

Another drawback of current practices addressed by the ACB system involves estimates of job gains produced by policies or projects. Politicians and bureaucrats continually announce that their pet projects will create tens of thousands of jobs. However, if these numbers were accurate, governments could eliminate unemployment simply by introducing more and more new programs. These projections rarely account for job losses arising from the taxes which must be imposed to finance programs. The ACB computer program includes calculations of job losses caused by tax increases.

Finally, the failure to determine costs and benefits can often stifle negotiations for mutually beneficial compromises, and renders the political process more susceptible to manipulation by special interests with superior resources.

The above deficiencies are particularly costly in these times of budget deficits and cutbacks.

II. THE SOLUTION

1. Introduction

The ACB Computerized Cost-Benefit Analysis System is a modular menu driven computer program which takes data from previously published studies and produces several tallies of costs and benefits arising from government policies. It can significantly reduce the time and money needed to determine costs and benefits, while increasing the scope and accuracy of the analyses. The system allows the policymaker to change assumptions, and to add costs and benefits. It can also serve a bibliographic function--rapidly leading analysts to sources of information.

The system asks the user to select:

1) A Policy Area (such as CRIME, ENVIRONMENT, or HOUSING),

2) A Function To Be Performed (e.g. VIEW/ALTER COST BENEFIT TALLIES, or ENTER DATA),

3) The Amount Of The Proposed Expenditure,

4) The Geographic Region Under Analysis,

5) A Specific Policy (such as HIRING POLICE or INCREASING THE SEVERITY OF SENTENCES).

If VIEW/ALTER COST BENEFIT SUMMARIES is chosen, the system presents the policymaker with several possible scenarios. The scenarios provide different means to estimate costs and benefits. For crime the rows of cells within the scenarios:

1) present coefficients from studies showing the extent to which a policy such as the hiring of police tends to produce an effect, say increase arrests or convictions.

2) presents coefficients found in studies measuring the extent to which the change in the effect (increases in arrests or convictions) changes the level of a disamenity (e.g. crime), and

3) multiplies (1) and (2) resulting in the extent to which a policy cuts the disamenity

4) multiplies the results in (3) by estimates of the costs imposed on society by the disamenity (crime), which comprise the benefits of a policy.

5) adds in the effects of government spending multipliers

6) compares the benefits determined above to costs

Alternative scenarios for measuring costs and benefits are generated. For crime, coefficients are presented from studies which directly measure the effects of law enforcement expenditures upon crime, and of policies upon convictions rather than arrests, and then of convictions upon crime. Additional scenarios are derived by measuring the costs of crime in different ways, including a) direct dollar losses, b) changes in property values, c) wage premiums demanded by employees faced with disamenities, and d) willingness to pay for reductions as expressed in surveys. Further scenarios arise from different disaggregation schemes.

As Figure 1 below shows the system:

1) contains a database filled with coefficients and other information derived from previous studies.

2) converts the units of each study into a common base.

3) places the data from studies which investigate the same phenomena together by attaching a variable name to each result in the database.

4) derives a single representative (weighted average) number for each variable by weighting the elements of the studies. The system provides a number of potential weighting schemes, and allows the user to modify the weights. One scheme attaches greater significance to studies performed in later years (in terms of data and/or publishing date), and also utilizes weights based on the apparent quality of the study and the plausibility of results.⁽¹⁾

5) produces a series of potential cost benefit scenarios looking at causes and effects, as well as costs and benefits, in different ways based on the weighted variables.

The chart below describes the general operation of the system.

FIGURE 1

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2. Data Sources

The information used for this database consists of regression coefficients, survey results, and cost estimates derived from studies previously published in academic journals, and by official government agencies. The academic journals include the American Economic Review, the Journal of Economic Literature, the Journal of Political Economy, the Review of Economics and Statistics, the Quarterly Journal of Economics, the Journal of Environmental Management, the Review of Economic Studies, the Journal of Public Economics, Land Economics, the Journal of Urban Economics, the Journal of Contemporary Policy Studies, Criminology, the Journal of Quantitative Criminology, and the Journal of Crime and Delinquency

3. Difficulties

Obviously, the heterogeneity of costs, benefits and policies introduces many difficulties. Furthermore, published cost benefit studies are rare, often fail to present critical information, and are very diverse in terms of assumptions, time periods, units, functional form, etc.

The complexity of the task can be illustrated by examining the costs and benefits of law enforcement expenditures. The benefits of an increase in police include not only reductions in crimes, but better traffic flows, and improved emergency services.

In addition, crimes reported to police are well below the number of crimes found though surveys. Furthermore, the effect of police upon crime can be estimated in a number of ways. Analysts have measured the decrease in the total crime rate directly by correlating the total crime rate and police per capita; by looking at the effects of police upon arrests and then at the effects of arrests upon crime; and/or by determining the effects of police upon convictions and the effects of convictions upon the crime rate. Some researchers have disaggregated each of these effects by type of crime (e.g. burglary and robbery).

Similarly, costs can be measured directly by tallying the economic costs of each crime (the value of goods stolen or damaged), anti-theft device costs per crime, incarceration costs per crime, and judicial costs per crime. However, direct measurements cannot account for one of the greatest costs--fear. Thus, costs may better be measured by looking at the effects of crime upon property values after holding other factors constant, wage premiums accorded to jobs involving location in higher crime areas, or willingness to pay as stated in surveys.

Cost benefits studies and regression analyses are also rarely easy to compare. Studies of crime reductions can be conducted in linear or in logarithmic terms. They cover different time periods and geographic areas. In addition, both the dependent and independent variables are far from homogeneous, as some studies look at total crimes, others analyze property crimes, and still others only murders. Independent variables include law enforcement expenditures, expenditures on police, and the police force. Theoretical disputes can also create difficulties. Finally, policy necessarily involves normative considerations, which cannot help but influence results.

Other items of interest, such as environmental damage, are by their nature even more heterogeneous, involving thousands of chemicals, dozens of diseases, and other costs.

The system attempts to overcome these difficulties through conversion algorithms.

III. OPERATION OF THE SYSTEM--USER ENTRIES

Introduction

The following describes the operation of the system. A step by step printout of the screens in a typical run is presented in Appendix I. The reader may wish to look at a typical run now, to see how the system works, before studying the rest of this manual.

1. Entering the System

In order to enter the system, the user simply logs on to LOTUS and opens the program CBEXEC.

2. Description

The user is then asked if he/she wants a description of the system.

If the response is affirmative, the user may then view a description similar to that outlined above by pressing the cursors or PAGE DOWN keys. When finished with the description the user presses the RETURN key.

3. Selection of Policy Type

The user is then asked to select a policy category: Crime, Environment, Housing, Fire, Transportation, or Taxation. Only the first two categories are currently operational.

4. Selection of Operation

The ACB Social Cost benefit analysis system allows the user to:

VIEW/ALTER SUMMARIES of Cost Benefit Analyses. Upon selection of this option the user can view or change summaries of costs and benefits for particular policies. If this item is selected the user is asked for additional information.

ENTER DATA allows the user to enter data from additional studies or to change previous entries. If this option is selected the user is placed within the selected database and then may enter data.

CHANGE WEIGHTING. This choice allows the user to emphasize the results of particular studies based upon the date of the study, place of the study, and other factors.

VIEW STUDIES permits you to examine summaries of the studies used to derive the cost benefit summaries. This category allows the user to view the coefficients, authors, significance test results, date of study, time period of study, geographic areas covered, categories of the results. Another option lets the user see the publication in which the study appeared, the title of the work, and other facts. The user may select or sort the data in a number of different ways, and is prompted for criteria to sort or select information for printouts from the basic databases.

The operations are discussed more fully below.

A. VIEW SUMMARIES

a. Enter Additional Information

If VIEW/ALTER SUMMARIES is selected, additional information may be entered so as to tailor the results to specific needs.

5. ENTER PROPOSED EXPENDITURES. This prompt permits the user to enter the costs incurred by a policy which partially determines the extent of the benefits derived from a policy (in conjunction with the next entry--CURRENT EXPENDITURES). The entry is optional if the user wants limited results. In conjunction with the entry of current expenditures. Higher expenditures can result in reduced benefits if decreasing returns to scale is assumed, or greater benefits if increasing returns to scale is assumed. The ACB system estimates benefits assuming increasing and decreasing returns to scale. If exact costs are not known, but the user wishes to see the effect of a 10% increase she may wish to enter a 1 in this category and a 10 for current expenditures.

This entry may be superseded by entry 8 (SOURCES TREATED). Thus, if the user specifies that 1,000 prisoners are to be treated with intensive therapy the program automatically specifies costs.

6. ENTER CURRENT EXPENDITURES. This prompt permits the user to enter total current expenditures, which partially determines the extent of the benefits derived from a policy in conjunction with the previous entry (PROPOSED EXPENDITURES). The entry is optional if the user wants limited results. In conjunction with the entry of proposed expenditures this entry can result in reduced benefits if decreasing returns to scale is assumed If exact costs are not known, but the user wishes to see the effect of a 10% increase he may wish to enter a 1 in this category and a 10 for current expenditures. If the user enters a -1 the database will look up current expenditures from an internal database.

7. ENTER CURRENT CRIME RATE. This prompt permits the user to enter total current expenditures which partially determines the extent of the benefits derived from a policy in conjunction with other entries. The entry is optional if the user wants limited results. In conjunction with the entry of proposed and current expenditures this entry can result in reduced benefits if decreasing returns to scale is assumed. Hiring police officers, will probably produce greater benefits in an area with relatively high crime rates than in a low crime rural area. If the user enters a -1 the database will look up current crime rates in an internal database.

8. ENTER NUMBER OF SOURCES TREATED. For crime, this prompt permits the user to enter the number of prisoners treated with intensive therapy, the number of drug addicts placed in rehabilitation programs, etc. For pollution, this entry reflects the number of boilers or production plants treated. The program can then calculate costs and benefits of policies based upon information in the database.

9. SELECT REGION. Results from studies and raw data vary from place to place. This entry allows the user to select information from a particular geographic area. It is not yet fully operational so the user must select "U.S.". Specification of Region may be important because application of police officers or pollution equipment to New York City with relatively high crime rates and pollution levels may produce greater benefits than hiring of police or use of pollution control equipment in a low crime, low pollution rural area. Eventually, data from particular regions with respect to effects of particular policies, or with respect to key variables in calculating costs and benefits (such as wages and costs) will be pulled.

10. SELECT DISPLAY FORMAT. The user must next choose to print out results on a printer or simply view data on the screen.

11. SELECT POLICIES. Finally, the user may select the specific type of policy. For crime, the user may want to see the following policies

1. Spending on Police

2. Hiring Police

3. Increase Certainty of Punishment

4. Provide Intensive Therapy to Prison Inmates

5. Give Unemployment Insurance to Prisoners Upon Release from Prison

6. Increase Severity of Punishment

7. All of the Above

For the environment, the user may want to compare the benefits and costs of installing devices in utility boilers designed to reduce sulfur dioxide, or suspended particulates, etc.

12. MODIFY TALLIES. If the user wishes to modify tallies he or she specifies C when prompted, and then uses LOTUS commands to change the tally spreadsheet as desired. The file may then be specified under a different name and retrieved when needed.

The system then prints out several summaries of scenarios which offer different assumptions with respect to measuring effects of policies and costs. The output is described below.

B. ENTER DATA

Upon selection of this item the user can enter or change data (including coefficients of regressions, cost data, authors, etc.) from individual studies, and then reweight the variables.

C. CHANGE WEIGHTING

This selection allows the user to change the degree to which certain factors such as t-statistics, consistency with theory, year of the study, year of the data, etc. are emphasized in weighting studies.

D. VIEW STUDIES

This category allows the user to view the coefficients, authors, significance test results, date of study, time period of study, geographic areas covered, categories of the results, variable names, etc. of the studies used to derive cost benefit summaries. The user may sort the studies in a number of different ways.

The system can serve as a bibliographic reference source for further study.

IV. OUTPUT--RESULTS--PRINTOUT

Output from the system may not be easy to understand due to the difficulties inherent in cost benefit analysis described above. Professional experience with cost benefit analysis, and practice with this system is generally needed to interpret the results.

A. VIEW SUMMARIES

Policies, such as increased police expenditures, are shown at the top of columns. The left side of each row presents specific effects (costs and benefits), such as reduced burglaries. As one moves down the rows within a column the user can view the weighted average of the results produced by the studies.

Benefits are presented first. Categories for benefits vary from policy to policy. However, direct benefits are generally, presented first, then other benefits resulting in, say, changes in property values are shown.

The form of the presentation is dictated by the nature of the studies.

Detailed descriptions of the output follows:

I. CRIME

The system disaggregates studies by type of crime because many studies examine the effects of policies only upon murder, or robberies, or burglaries. Disaggregated studies permit a more in-depth understanding of the process by which policies impose costs or produce benefits, and increase the accuracy of conclusions. Studies which report effects on all crimes are presented first, then studies which disaggregate effects by type of crime are shown.

PAGE 1

BENEFITS

% Change in Effect per 1% Change in Policy--Coefficient

The primary effect of a 1% change in policy is first presented. The effect is presented in the form of a coefficient located in the cells between column and row headings. Thus, a 1% change in expenditures may increase arrests by 2%. The increase in arrests is not a direct benefit, but may serve to deter crime. The policy is shown at the top of the columns. The category of the variable affected (say, property crimes) and the type of effect (e.g. the effect of arrests per crime on crimes per capita) is shown in the left corner.

The precise nature of the effect presented can be determined through the variable name, directly below the coefficient and the description near the column headings. The user can print variable definitions after the summaries. The variables are defined as follows:

Crime Category : Effect . Units - Policy . Units

Thus for A:A.C-OX.P

The first A implies that the effect refers to all types of crimes

The second A says that the effect examined in the studies with results for this variable is Arrests. Other studies may analyze the effects of policies directly upon the crime rate.

The C refers to units for the effects, which in this case is reported Crimes. Thus, the effect of the policy considered is A.C--arrests per crime reported. Other studies may show effects in terms of A.P--arrests per capita.

OX refers to the type of policy--Police Expenditures.

The P refers to units for the policy--per capita in this case.

The : . and - are simply delimiters separating the prefixes and suffixes.

The data for this variable are derived from published regression analyses.

% Change in Crime per 1% Change in Effect--Coefficient

The above section only reported the direct effect of a policy, which does not, in and of itself, necessarily produce a benefit. The row analyzes the impact of the change in the effect of the policy, say increased arrests, upon the actual benefit--the reduction in crime. The variables in this section are defined in ways similar to that presented above.

% Change in Crime per 1% Change in Policy

This line multiplies the two above effects, or presents the results of studies which directly analyze the effects of a policy upon the final effect--say increased crime. Thus, when reading the results of this line, the user can determine that, say, a 1% increase in expenditures on police, results in a 1% decrease in crime.

EFFECTS OF REHABILITATION/PREVENTION PROGRAMS

Several studies of rehabilitation or prevention programs compare crime rates or recidivism rates between individuals involved in programs and control groups. We can estimate the percent change in crime resulting from all criminals treated by the program from the difference in recidivism rates by multiplying the Difference in Recidivism Rates by the Contribution of Criminals Treated to the Crime Rate. The Contribution of Criminals Treated to the Crime Rate is determined by multiplying the number of individuals treated (entered by the user) by the average crimes per criminal, and then dividing the result by the total number of crimes committed.

COSTS OF CRIMES

Direct Crime Costs

This section examines the direct, tangible costs of crimes. These costs can then be multiplied by the effect of policies upon crime to derive a direct benefit from a policy.

The most direct costs are those directly incurred by the victim. For burglaries, robberies, and muggings the direct costs are the value of property stolen.

Anti-theft Device Costs Per Crime

Higher crime rates induce individuals to spend more upon anti-theft devices. Lower crime rates will presumably lower these costs and represent a benefit to society. This cell reports the average spending on these items per crime based upon previous studies.

Incarceration Costs Per Crime

Policies may increase or decrease incarceration costs. They may increase the cost of crime to the criminal, and thus reduce the crime rate and incarcerations--or they may increase arrest rates, and thus increase incarceration costs. These costs can be very high--$30,000 or more per criminal jailed. Once again results from previous studies are aggregated. Because criminals generally commit several crimes, and are often not caught, costs per crime are much lower than costs per criminal jailed.

Judicial Costs Per Crime

Higher crime rates and higher arrest rates, require more judges, more assistant district attorneys, more clerks, etc, which should be considered when evaluating any crime policy.

Total Direct Costs

This cell aggregates the four direct costs presented above.

CHANGE IN DIRECT COSTS/VICTIM PER 1% CHANGE IN POLICY

The cell multiplies total direct costs per crime derived above by the percent change in crime per 1% change in policy derived above.

Victimization Rate

Because costs above are reported per crime rather than per household the above figures must be multiplied by the victimization rate to derive costs per household. The victimization rate is pulled from a separate database of information comprised of data from government publications.

CHANGE IN DIRECT COSTS/HOUSEHOLD PER 1% CHANGE IN POLICY

The cell multiplies total direct costs per crime per victim derived above by the victimization rate.

PAGE 2

DISAGGREGATED ANALYSIS

The cells that follow below on page 2 evaluate the same variables:

1) % Change in Effect per 1% Change in Policy--Coefficient

2) % Change in Crime per 1% Change in Effect--Coefficient

3) % Change in Crime per 1% Change in Policy

COSTS OF CRIMES

4) Direct Crime Costs

5) Anti-theft Device Costs Per Crime

6) Incarceration Costs Per Crime

7) Judicial Costs Per Crime

8) Total Direct Costs

9) CHANGE IN DIRECT COSTS/VICTIM PER 1% CHANGE IN POLICY

10) Victimization Rate

11) CHANGE IN DIRECT COSTS/HOUSEHOLD PER 1% CHANGE IN POLICY

but for different categories of crime--Property Crimes, Personal Crimes, Robberies, Burglaries, Larcenies, Auto Thefts, Murders, Rapes, and Assaults. This disaggregation is used because many of the best studies consider only specific types of crimes.

TOTAL CHANGE IN DIRECT COSTS/VICTIM PER 1% CHANGE IN POLICY

The cell tallies costs from the disaggregated and aggregate direct costs.

PAGE 3

OTHER COSTS OF DISAMENITITES

Direct tangible costs may be a small part of the costs to society of crime, and the benefits of crime reduction. The fear of crime, and the psychic damage resulting from an actual crime, may be far more costly than the actual dollar losses. After all, the direct dollar losses incurred in rapes are usually zero, but the psychic costs may be infinite.

Obviously, intangible costs are hard to measure. There is no market to price fear.

Economists have circumvented the lack of markets by looking at changes in property values and wages associated with increases in crime through regression analyses that hold other variables constant. Buyers and sellers of homes presumably take into account the value of reduced fear of crimes as well as the direct costs of crime. Similarly, employees will demand more in wages and benefits to work in areas suffering from various disamenities.

PROPERTY VALUES

% Change in Property Value per 1% Change in Crime

These cells report the regression coefficients from studies evaluating the change in property values for every 1% change in crime.

% Change in Property Value Per 1% Change in Policy

The change in property values per 1% change in crime does not measure the benefits of policy, because there is not a 1:1 relationship between changes in crime and changes in policy. Therefore this cell multiplies the % Change in Property Value Per 1% Change in Crime above by the % Change in Crime per 1% Change in Policy derived above, unless the results are available directly.

Total Change in Property Value Per 1% Change in Policy/Household

This cell multiplies the percentage change in Property Value derived above by the Median Property Value in the region under analysis to arrive at a dollar loss figure. Median Property Values are stored in an ACB database.

Total Change in Property Value Per 1% Change in Policy/Household/Year

Because the property value change derived above is a stock and every other number is an annual flow, this change in total property value above is not comparable to other figures. We therefore estimate annual flows by determining the payments per year equivalent to the property value over a given time period and using a given discount rate.

WAGES

% Change in Wages Value per 1% Change in Crime

These cells report the regression coefficients from studies evaluating the change in wage premiums needed to compensate workers for every 1% increase in crime.

% Change in Wages Per 1% Change in Policy

This cell multiplies the % Change in Wages Per 1% Change in Crime above by the % Change in Crime per 1% Change in Policy derived above, unless the results are available directly.

Total Change in Wages Per 1% Change in Policy/Household

This cell multiplies the percentage change in Wages derived above by Median Annual Wages in the area to arrive at a dollar loss figure.

WILLINGNESS TO PAY

% Change in Willingness to Pay per 1% Change in Crime

Survey data can provide another indication of the costs imposed by crime. Surveys ask how much respondents would be willing to pay for a reduction in crime.

Total Change in Willingness to Pay Per 1% Change in Policy

This cell multiplies the % Change in Willingess to Pay Per 1% Change in Crime above by the % Change in Crime per 1% Change in Policy derived above.

TOTAL BENEFITS/HOUSEHOLD PER 1% CHANGE IN POLICY

This cell sums all costs above where appropriate to derive the total benefit per household for a 1% change in policy.

TOTAL BENEFITS/HOUSEHOLD OF PLANNED EXPENDITURES

This cell presents the sum in terms of benefits per household for the total planned expenditure. Total planned expenditures are entered by the user (see above). Currently a linear extrapolation is used. Ideally a nonlinear function based on levels of crime and expenditure should be utilized.

Government Expenditures Multiplier

Government expenditures may create additional jobs, income, and tax dollars through the multiplier effect, or reduce these variables by crowding out private expenditures. Many studies have examined the impact of expenditures upon jobs and income. This section aggregates the results of some of these studies. The ACB program can eventually be linked to an econometric or Input/Output model to provide this data.

Benefits from Multiplier

These cells multiply the total proposed expenditures by the multiplier.

TOTAL BENEFITS PER HOUSEHOLD

This category adds all previous benefits and provides a display of benefits per household.

TOTAL BENEFITS PER HOUSEHOLD

This category tallies benefits for all households.

TOTAL BENEFITS ASSUMING INCREASING/DECREASING RETURNS

This cell attempts to account for potential nonlinearities in benefits based on size of expenditures and/or the size of the problem treated.

COSTS

Direct Tax Costs

These costs are entered by the user after a system prompt. The program places the entered value in the appropriate cell.

Other Direct Costs which may be entered by the user include the following:

Capital Costs
Administrative Costs
Financing Costs
Repairs and Maintenance
Salaries

Program Costs

Some studies have examined the costs and benefits of particular programs, such as drug rehabilitation, intensive therapy in prison, providing unemployment insurance to prisoners upon release from jail, etc. The next section of the sheet examines and aggregates costs per source treated and multiplies the results by the number of sources treated as entered by the user.

Marginal Welfare Cost of Taxation--Labor Supply Change

Taxes used to pay for programs can alter labor supply decisions and reduce welfare. These cells account for the marginal welfare cost based upon previous studies.

Participation Costs

Some programs, like neighborhood crime watches, or "workfare" require participants to sacrifice time or resources. These costs are included here.

Tax Multiplier

Studies often proclaim huge benefits for programs due to government spending and job creation multipliers, but fail to account for the costs of alternative uses of tax dollars. The tax multiplier accounts for the economic costs imposed by taxes.

Absolute Changes From Tax Multiplier

The Tax Multiplier must be multiplied by total costs to derive the ultimate tax multiplier effect.

TOTAL COSTS PER HOUSEHOLD

This cell sums all of the above costs.

NET BENEFITS

TOTAL BENEFITS/TOTAL COSTS

This item is the ratio of total benefits calculated above to total costs calculated above.

TOTAL BENEFITS - TOTAL COSTS

This item presents the ultimate aim of the program--the net benefits of the program.

EXCLUDING MULTIPLIERS

TOTAL BENEFITS/TOTAL COSTS

TOTAL BENEFITS - TOTAL COSTS

Because many of the benefits and costs in preliminary analyses arise from multiplier effects, we have also subtracted the multiplier effects from the total in the summary.

Memo: Jobs Created/lost Government Expenditure

Taxes

Policymakers often place a special value upon jobs. This items presents the effects of programs upon jobs.

Memo: Inflation Generated Government Expenditure

Taxes

National policies can create inflation. This item reports the inflation generated.

II. ENVIRONMENT

Many of the categories in the Environmental Sector are the same as those in the Crime Sector, but some differ.

Instead of disaggregation by type of crime, the program disaggregates costs by type of effect. Direct effects may be in terms of cardio- respiratory disease, basic aesthetic losses, etc. The pollutant is shown at the top of the columns. The category of the variable affected (say, cardio respiratory disease) is shown on the left side.

PAGE 1

The first step in determining the costs and benefits of anti-pollution policy is to derive the percent change in pollution per 1% change in policy. This involves, first estimating the percentage of pollution generated by the source treated (say utility boilers) based upon EPA data. Next, we determine the percentage of units treated by the program based upon user entries and data from the U.S. Department of Energy on the total number of sources. Finally, the Efficiency of the Policy Instrument, generally available from the E.P.A. is considered. All three of these numbers: (1) The percentage of pollution generated by the source treated, (2) the percentage of units treated, and (3) the Efficiency of the Policy Instrument are multiplied in arriving at the percent change in pollution for a given policy.

The benefits of these reductions are derived from eight health categories:

(1) Deaths,

(2) Infant Mortality,

(3) Chronic Respiratory Disease Cases,

(4) Total Cardiac and Respiratory Admissions,

(5) Total Cardiac Admissions,

(6) Total Respiratory Admissions,

(7) Reduced Activity Days, and

(8) Minor Reduced Activity Days.

For each of these categories we consider the following breakdowns to arrive at an estimate of the change in costs for a given change in policy.

BENEFITS

% Change in Effect per 1% Change in Pollution-Coefficient

The primary effect of a 1% change in pollution is first presented. The effect is presented in the form of a coefficient located in the cells between column and row headings. Thus, a 1% change in sulfur dioxide may increase cardio-respiratory disease by 2%.

The precise nature of the effect presented can be determined through the variable name, directly below the coefficient. The user can print variable definitions after the summaries. The variables are defined as follows:

Disease - Pollutant

Thus for CRA-SO2

CRA is the code for Cardio Respiratory Disease

SO2 is the code for Sulfur Dioxide Pollution

The - is simply a delimiter separating the prefixes and suffixes.

CRA-SO2 depicts the change in Cardio Respiratory Diseasers resulting from changes in Sulfur Dioxide pollution.

The data for this variable are derived from published regression analyses.

% Change in Pollution per Change in Policy--Coefficient

This cell multiplies the % change in effect per 1% change in pollution by the % change in pollution for a given change in policy, both of which are described above.

A dollar value must now be attached to this benefit. We attach dollar values by multiplying the percent change in pollution per 1% change in policy by--wages lost, costs of medical care, and/or values obtained from surveys in deriving direct costs per victim. The costs per victim must be multiplied by the frequency rate of the effect (say chronic respiratory disease) per household in determining the costs per household.

The dollar value for each of the eight health categories listed above--

(1) Deaths,

(2) Infant Mortality,

(3) Chronic Respiratory Disease Cases,

(4) Total Cardiac and Respiratory Admissions,

(5) Total Cardiac Admissions,

(6) Total Respiratory Admissions,

(7) Reduced Activity Days, and

(8) Minor Reduced Activity Days.

is determined for two pollutants affected by the policy and the results are summed.

Other scenarios are generated by looking at studies which directly estimate work days lost and medical costs from pollution.

OTHER COSTS OF DISAMENITITES

As with crime, direct tangible costs may be a small part of the costs to society of pollution, and the benefits of pollution reductions. The psychic damage from illnesses and the aesthetic costs of smoke and other pollutants may outweigh the actual dollar losses. In addition, direct costs from diseases may be difficult to measure.

Economists have measured intangible costs by looking at changes in property values and wages associated with increases in crime through regression analyses that hold other variables constant. Buyers and sellers of homes presumably take into account the value of reduced pollution as well as the direct costs. Similarly, employees will demand more in wages and benefits to work in areas suffering from various disamenities.

PROPERTY VALUES

% Change in Property Value per 1% Change in Pollution

These cells report the regression coefficients from studies evaluating the change in property values for every 1% change in pollution.

% Change in Property Value Per 1% Change in Policy

The change in property values per 1% change in pollution does not measure the benefits of policy, because there is not a 1:1 relationship between changes in pollution and changes in policy. Therefore this cell multiplies the % Change in Property Value Per 1% Change in Pollution above by the % Change in Pollution per 1% Change in Policy derived above, unless the results are available directly.

Total Change in Property Value Per 1% Change in Policy/Household

Total Change in Property Value Per 1% Change in Policy/Household/Year

WAGES

% Change in Wages Value per 1% Change in Pollution

These cells report the regression coefficients from studies evaluating the change in wage premiums needed to compensate workers for every 1% increase in pollution.

% Change in Wages Per 1% Change in Policy

This cell multiplies the % Change in Wages Per 1% Change in Pollution above by the % Change in Pollution per 1% Change in Policy derived above, unless the results are available directly.

Total Change in Wages Per 1% Change in Policy/Household

This cell multiplies the percentage change in Wages derived above by Median Annual Wages in the area to arrive at a dollar loss figure.

WILLINGNESS TO PAY

% Change in Willingness to Pay per 1% Change in Pollution

Survey data can provide another indication of the costs imposed by pollution. Surveys ask how much respondents would be willing to pay for a reduction in pollution.

Total Change in Willingness to Pay Per 1% Change in Policy

This cell multiplies the % Change in Willingess to Pay Per 1% Change in Crime above by the % Change in Pollution per 1% Change in Policy derived above.

TOTAL BENEFITS/HOUSEHOLD PER 1% CHANGE IN POLICY

This cell sums all costs above where appropriate to derive the total benefit per household for a 1% change in policy.

TOTAL BENEFITS/HOUSEHOLD OF PLANNED EXPENDITURES

Government Expenditures Multiplier

Benefits from Multiplier

These cells multiply the total proposed expenditures by the multiplier.

TOTAL BENEFITS PER HOUSEHOLD

This category adds all previous benefits and provides a display of benefits per household.

TOTAL BENEFITS ASSUMING INCREASING/DECREASING RETURNS

This cell attempts to account for potential nonlinearities in benefits based on size of expenditures and/or size of the problem.

COSTS

DIRECT COSTS

Direct Costs are obtained from EPA studies, and are placed into comparable units

If available, costs are disaggregated into Direct, Administrative, Capital, Maintenance, Utilities, Payroll, and Financing.

Most pollution costs abatement data is available in terms of costs per unit of production. In deriving total costs we multiply unit costs by total production. Total production is derived by multiplying the user entry for number of sources treated by average unit costs after rendering units comparable.

Marginal Welfare Cost of Taxation--Labor Supply Change

Taxes used to pay for programs can alter labor supply decisions and reduce welfare. This cell accounts for the marginal welfare cost based upon previous studies.

Tax Multiplier

Studies often proclaim huge benefits for programs due to government spending and job creation multipliers, but fail to account for the costs of alternative uses of tax dollars. The tax multiplier

Absolute Changes From Tax Multiplier

The Tax Multiplier must be multiplied by total costs to derive the ultimate tax multiplier effect.

TOTAL COSTS PER HOUSEHOLD

This sell sums all of the above costs.

NET BENEFITS

TOTAL BENEFITS/TOTAL COSTS

This item is the ratio of total benefits calculated above to total costs calculated above.

TOTAL BENEFITS - TOTAL COSTS

This item presents the ultimate aim of the program--the net benefits of the program.

EXCLUDING MULTIPLIERS

TOTAL BENEFITS/TOTAL COSTS

TOTAL BENEFITS - TOTAL COSTS

Because many of the benefits and costs in preliminary analyses arise from multiplier effects, we have also subtracted the multiplier effects from the total in the summary.

Memo: Jobs Created/lost Government Expenditure

Taxes

Policymakers often place a special value upon jobs. This items presents the effects of programs upon jobs.

Memo: Inflation Generated Government Expenditure

Taxes

National policies can create inflation. This item reports the inflation generated.

V. THE PROGRAM

The ACB Computerized Cost Benefit Analysis System consists of several modules in spreadsheet form which are activated by user entries. All instructions currently use LOTUS commands. In order to enter the system, the user simply logs on to LOTUS and opens the program CBEXEC.WK3. CBEXEC.WK3 determines which module to activate based upon the user's entry of a Policy Category (e.g. Crime, Environment, Housing, Fire, Transportation, or Taxation), and an operation. Operations include the following:

VIEW/ALTER SUMMARIES Allows the user to view or change summaries of costs and benefits for particular policies. This activates the program CBCRTD.WK3 if the user choses to look at crime policies, or CBCENTD.WK3 if the user choses environmental policies. Each of these programs contains formats for calculating costs and benefits. These programs initially pull the program CBTALPRG.WK3 which contains instructions common to all tally programs. They then pull Variable Definitions and other data. The programs pulls and tallies weighted averages of variables in the databases.

ENTER DATA allows the user to enter data from additional studies or to change previous entries. If this option is selected the user is placed within the selected database CBCRIMD4.WK3 for crime, and CBENVID4.WK3 for the environment. Data is entered and the variables may be reweighted. If the user chooses to reweight variables the program CBWEIG.WK3 is opened to perform this task. Upon completion of the reweighting the tally programs--CBCRTD.WK3 and CBENTD.WK3--are retrieved and the weighted variables are placed back into these programs.

CHANGE WEIGHTING. This choice allows the user to emphasize the results of particular studies based upon the date of the study, place of the study, and other factors. CBWEIG.WK3 is opened to perform this task. Upon completion of the reweighting the tally programs--CBCRTD.WK3 and CBENTD.WK3--are retrieved and the weighted variables are placed back into these programs.o

VIEW STUDIES permits you to examine summaries of the studies used to derive the cost benefit tallies. This category allows the user to view the coefficients, authors, significance test results, date of study, time period of study, geographic areas covered, and categories of the results. If this option is chosen the program CBVIEWEN.WK3 is retrieved. CBVIEWEN.WK3, in turn, pulls raw data from CBCRIMD4.WK3 for crime or CBENVID4.WK3 for the environment, and presents the user with various sorting and selection options to view the data.

Another option lets the user see the publication in which the study appeared, the title of the work, and other facts from the program CBBIBL2.WK3.

SCREENS DISPLAYED BY THE PROGRAM--ENTRIES REQUIRED

1. The need for weights based on plausibility of results can be shown through an example from the crime literature. Many studies, even well specified two staged least squares analyses, show that law enforcement expenditures actually increase the crime rate. This anomaly probably results largely from increased reporting of crimes when expenditures rise. Because such results violate theoretical expectations as well as common sense, they were given lower weights. Other studies were given lower weights because they are clearly inferior with respect to technical sophistication, quality of data, scope of analysis, number of factors held constant, etc.