AuthorOren-Kolbinger, Orli
  1. INTRODUCTION: DOES A JUDGE'S PERSONAL AND PROFESSIONAL 581 BACKGROUND INFLUENCE DECISIONS IN TAX CASES? II. THE SOCIAL BACKGROUND MODEL 587 A. General 587 B. Personal Background Parameters of Judges 589 1. Gender 589 2. Age 592 3. Race and Ethnicity 592 4. Religious Beliefs 594 C. Professional Background Parameters of Judges 594 1. Previous Occupation 594 2. Seniority 595 D. Ideology 596 E. Complementing the Empirical Background: Judges' 597 Backgrounds and Tax Judicial Decision-Making III. METHODOLOGY 598 A. The Legal Process 598 B. Collecting Data 599 C. The Regression Variables 600 1. The Dependent Variable: The Acceptance Level of the 600 Taxpayer's Claim 2. Explanatory Variables 601 3. Control Variables 602 D. Hypotheses 603 1. Gender 603 2. Previous Occupation 603 3. Seniority 604 4. Age at the Time of the Decision 604 5. Age at the Time of Appointment 604 IV. RESULTS 604 A. Descriptive Statistics 604 B. Econometric Analysis--Ordinal Regression 608 1. General 608 2. Regression Model Results 611 V. ANALYZING THE RESULTS 614 A. Interpreting the Results 614 B. Comparing the Results of the Ordinal Regression Model 616 with the Results of a Logistic Model and a Multinomial Model VI. SUMMARY 619 I. INTRODUCTION: DOES A JUDGE'S PERSONAL AND PROFESSIONAL BACKGROUND INFLUENCE DECISIONS IN TAX CASES?

    Predicting legal outcomes and identifying variables that underlie the judicial decision-making process has social and public value. For many years now, legal scholars, economists, and political scientists dealt with the question of how judges with different characteristics, including gender, professional background, and policy preferences, determine legal out-comes. (1) In this Article, I provide an empirical examination of this question in the tax context--an area that has received relatively less focus than other legal fields--that could be implemented in various tax jurisdictions. I do so by using an original sample of tax cases from Israeli district courts, which were decided during 1993-2012. Lastly, I advocate the use of a more fine-tuned method for coding the prevailing party in legal disputes.

    According to the social background model of judicial decisionmaking, judges' personal characteristics and professional experience affect judicial behavior. (2) Relying on this theory, I measure the influence of various explanatory variables on the acceptance level of the taxpayer's claim, meaning whether the judge sides with the taxpayer and overrules the IRS's decisions. These explanatory variables include gender, previous occupation, seniority, age at the time of appointment, and age at the time of the decision. The analysis also includes several control variables: the macroeconomic state of the market; the type of taxpayer, either individual or business; the district where the court resides; and whether the judge has a judicial specialization in tax cases, in other words is a "tax judge."

    I use the aforementioned variables to estimate the dependent variable, the level of acceptance of the taxpayer's claim. These claims are referred to in the Israeli context as tax appeals, therefore I will use this term for the rest of this Article. I coded the dependent variable as an ordinal, rather than binary, variable. While binary is the frequent coding method of the prevailing party variable, as evidenced by its use in previous studies, coding the variable as ordinal allows for the use of the ordinal regression model. Judicial decision-making is not necessarily binary. Therefore, coding the prevailing party in ordinal categories will better capture the judge's decision, leading to a more reliable analysis.

    In the past, the dominant theoretical approach of judicial decision-making was the legal reasoning model. (3) According to this model, judges' decisions rely on law, legislative intent, legal precedent, and logic. (4) Judicial decision-making was perceived as a good representation of existing law, depending on the facts of the given case. (5) Judges are supposed to follow the law in a uniform manner. (6) Neither judges' personal attributes nor past experiences should impact their judicial discretion. (7) Under the legal reasoning model, similar cases should be decided similarly by different judges because decisions are believed to be free from outside influences.

    Many empirical studies support the legal reasoning model. For example, Cross concluded that courts follow the rule of law after finding an existing high affirmance rate of federal district court decisions by the courts of appeals. (8) Songer et al. found that courts of appeals react to and follow Supreme Court precedent changes. (9) In an empirical study of 6,400 appeals, covering 24 legal areas, Sunstein et al. found that in some legal areas judges' decisions cannot be attributed to their ideological views. This might indicate that the rule of law was the dominant factor in these decisions. (10) Notably, Ashenfelter et al. reached similar conclusions with their study on federal district courts. (11)

    As a reaction to the legal reasoning model, other positive theories were developed to explain judicial decision-making. (12) Political scientists and legal scholars raised doubts about the law as a sole predictor of legal decisions. One of these theories, inspired by legal realism and behaviorism, is the attitudinal model, which proposes that judges' attitudes and policy preferences affect their decision-making. (13) Another example is the strategic model, which assumes that judges are rational actors who maximize their personal utility as they make their choices. (14)

    This study focuses on another positive theory of judicial decision-making, the social background model. (15) This model focuses on the question: are judges affected by their personal and professional attributes while making legal decisions? Per this model, certain non-legal parameters of judges, such as personal attributes and professional backgrounds, rather than the law itself, can explain their rulings. Under the social background model, these attributes help to better predict judicial outcomes.

    Although empirical legal studies have evolved over the last few decades, empirical knowledge from quantitative analysis of tax litigation and decision-making is still limited compared with other legal areas. (16) Moreover, this is the first research in the Israeli context that uses regression analysis to estimate the effect of judges' social background on their decisions in tax cases. (17)

    The motivation for this current research is two-fold: First, I use ordinal regression to analyze the measured effect on the prevailing party in tax cases. Very few researchers have taken this route before. (18) Many studies of judicial decision-making and tax litigation used logistic or multinomial regression, which are not always adequate for modeling legal reality. Using ordinal regression is possible because the dependent variable of the model--the acceptance level of the taxpayer's claim--accepts three (19) discrete values ordered in a legally meaningful way. (20) Comparing these three regression models--ordinal, logistic, and multinomial--shows that the coefficients from the ordinal regression model are the most statistically significant.

    Second, this research supplements the growing empirical legal study of tax law and tax litigation. The findings might also assist with a better understanding of legal proceedings that involve the government as a repeat player in court.

    The remainder of the Article consists of five parts. In Part II, I discuss the social background model, citing previous empirical studies as part of the theoretical discussion about judicial decision-making. I will complement this review of literature with previous empirical research about decision-making in tax cases. In Part III, I detail the methodology, including the background of the legal process, the data collection process, the regression variables, and the hypotheses. In Part IV, I provide descriptive statistics and present the results of the regression model. In Part V, I analyze the results and compare the ordinal regression results with the logistic and multinomial regression models' estimations. In Part VI, I conclude.


    1. General

      This research focuses on the social background model, which theorizes that a judge's social background might influence her or his decisions. Many empirical studies have already explored this issue, revealing that judges' personal attributes and professional backgrounds affect court decisions. Some of the studies also considered judges' ideology and policy preferences. (21) Personal attributes included age, gender, and race. Professional background included the judge's law school, professional position before appointment, and seniority. Policy preferences were usually measured by the political party of the nominating president or by ideological scores, when applicable. (22)

      Compared with those that focused mainly on ideology, empirical studies on the U.S. Supreme Court, which included parameters about the judges' backgrounds in addition to ideology, better predicted legal outcomes. (23) The studies that focused on ideology found that even though personal or professional attributes, especially the judges' previous occupation, influence judicial decisions, the effect is smaller than the influence of their ideology. (24) Even so, because ideology is correlated with other background variables, one might hypothesize that these other variables affect the evolvement of judges' ideology. (25)

      Empirical scholars found that personal and professional attributes affect judicial decision-making in various legal areas, including criminal law, search and seizure cases, employment law, sex- and race-based discrimination, sexual harassment, tax law, and economic regulation. (26) The results, however, were not always consistent. (27)

      Through the rest of this Part, I will review the main...

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