111 年 國立臺灣大學新聞學研究所《經濟學與新聞》

第 1 題

Read the following article and answer questions:

Is Driving Drunk Rational? by Stephen J. Dubner from Freakonomics on May 31, 2013

Benjamin Hansen, an economist at the University of Oregon whose work I've written about in the past, recently presented a conference paper that looks at this question in the case of drunk driving. Specifically, he examines whether people commit fewer crimes because of fear of what may happen to them if they do ("deterrence") versus what they've learned emotionally from punishments that have already happened to them (called "specific deterrence").

Hansen's study takes advantage of a large database of DUI (酒駕) offenders in Washington State, which has laws similar to the rest of the US. The key to the study is that there are two definitions of DUI: the regular old garden variety offence if BAC (血液酒精濃度) is over .08, and "aggravated" DUI with a level over .15. Aggravated DUI brings a harsher punishment for the offense in question, but it has no special effect on the level of punishment for the next offense (which rises in severity the same amount no matter the level of the prior conviction).

First, Hansen finds that having been convicted and punished for a DUI reduces the chances of getting caught with a DUI in the future. Since the punishment scale for DUI ramps up with prior convictions, this appears to fit with the standard theory that harsher punishment is a deterrent for reoffending.

However, one aspect of Hansen's findings calls the model of the rational criminal into question. Since there is no extra future penalty for those convicted of an aggravated DUI (compared to those convicted of minor offenses), if drunk drivers rationally calculated the future cost of punishment they would all have the same odds of reoffending regardless of the level of their past conviction. However, Hansen finds that those who got aggravated DUIs were actually less likely to reoffend, all else equal. This suggests that the experience of having received harsh punishment teaches you a lesson. This is called a "learning effect." Another implication is that drunk drivers may not fully understand the system of punishment, and base their estimation of the cost of the next conviction on past experience and not accurate knowledge of the law.

These findings are interesting in terms of both psychology and deterring crime. They suggest that increased sanctions for drunk driving—such as lower permissible BAC levels, longer license suspensions, ignition lock systems, and harsher fines—are indeed likely to have additional deterrent effects. In fact, Hansen computes that raising penalties by 10 percent would reduce drunk driving by about 4 to 7 percent, and this is just counting the effects on repeat offenders and not deterrence for those who have never been caught. However, there is one catch; the positive impacts of such a learning effect would take a while to play out, as the deterrent will only mount as people get caught and punished over time.

(A) [10%] Why does the author of this article (namely, Dubner) call the extra penalty from a past experience of the aggravated DUI is a "sunk cost"? Briefly explain.

(B) [15%] Specify the evidence found in Hansen's study against the hypothesis that drunk driving is rational? Briefly explain why it is opposing the hypothesis.

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這一題的完整詳解

本題主要在探討理性犯罪理論在酒駕行為上的適用性,特別是「威懾」(deterrence)與「學習效果」(learning effect)的概念。

(A) [10%] 題目詢問作者為何稱酒駕累犯的「額外懲罰」為「沉沒成本」(sunk cost)。
根據經濟學的定義,沉沒成本是已經發生且無法收回的成本,它不應該影響未來的決策。在「理性犯罪理論」中,犯罪者會權衡犯罪的預期收益與預期成本(包括被抓的機率與懲罰的嚴厲程度)來做決定。如果酒駕者是完全理性的,那麼過去的懲罰(無論是普通 DUI 還是加重 DUI)都應該被視為沉沒成本,不應影響他們對未來再次酒駕的決策。然而,文章提到「由於被判處加重 DUI 的人(相較於被判處輕微違規者)沒有額外的未來懲罰」,如果酒駕者是理性的,他們應該會因為未來的懲罰沒有差異而有相同的再犯機率。作者 Dubner 將「加重 DUI 的額外懲罰」稱為「沉沒成本」,是因為依據經濟學理論,這個「額外懲罰」已經發生,且對未來再犯的「直接」法律懲罰沒有造成額外影響,因此一個完全理性的犯罪者應該會忽略它,就像忽略過去的沉沒成本一樣,不影響其未來是否再犯的機率。
【答案】作者將過去的加重 DUI 額外懲罰稱為「沉沒成本」,是因為根據理性選擇理論,已經發生且無法收回的成本(即沉沒成本)不應影響未來的決策。在這種情況下,雖然加重 DUI 可能帶來較嚴厲的當下懲罰,但若對未來再犯的法律懲罰沒有造成額外影響,一個完全理性的酒駕者應該會忽略此額外懲罰,如同忽略其他沉沒成本一樣,而不影響其再犯的機率。

(B) [15%] 題目詢問 Hansen 的研究發現中有哪些證據,反駁了酒駕是「理性」行為的假設,並簡要說明理由。

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