📚 IB Economics: A Guide to Experimental Operations | IB 经济：实验操作指南
Economic experiments are no longer confined to research laboratories. In the IB Economics classroom, well‑designed experiments offer a powerful way to bring abstract theories to life — from supply and demand to game theory and behavioural biases. This guide walks you through the entire process of running an effective economics experiment, helping you turn hypotheses into hands‑on discovery while deepening your understanding of how real‑world agents behave.
经济学实验不再局限于研究实验室。在IB经济课堂上，精心设计的实验可以将抽象理论变为生动的体验——从供需关系到博弈论和行为偏差。本指南将带你走过开展有效经济学实验的全过程，帮助你把假设转化为亲手探索，同时加深你对真实世界行为主体如何行动的理解。
1. What Is an Economic Experiment? | 什么是经济学实验？
An economic experiment is a controlled environment in which participants make decisions under specified rules, incentives and information conditions. Unlike physical sciences where the objects of study are passive, economic experiments involve human subjects whose choices reveal preferences, strategic thinking and responses to incentives. The setup can be as simple as a double‑oral auction in a classroom or as structured as a computer‑based public goods game.
经济学实验是一个受控环境，参与者在明确的规则、激励和信息条件下做出决策。与自然科学中被动的客体不同，经济学实验涉及人类被试，其选择可以揭示偏好、策略思维以及对激励的反应。实验设置可以简单到课堂上的双口头拍卖，也可以结构化为基于计算机的公共物品博弈。
2. Why Experiment in IB Economics? | 为何在IB经济中开展实验？
Experiments serve three essential purposes in the IB Economics course. First, they make abstract models tangible: watching a market converge to equilibrium reinforces the concept of price signals far more effectively than a static graph. Second, they develop inquiry skills that support Internal Assessment commentaries by training you to frame testable questions and interpret real‑time data. Third, the new IB syllabus includes behavioural economics and game theory; experiments provide a natural entry point for exploring bounded rationality, social preferences and strategic interaction.
实验在IB经济课程中服务于三个重要目的。首先，它们将抽象模型具体化：目睹市场收敛至均衡比一张静态图表能更有效地强化价格信号的概念。其次，它们培养探究技能，通过训练你构建可检验的问题并解读实时数据，为内部评估评论提供支持。第三，新版IB大纲纳入了行为经济学和博弈论；实验为探索有限理性、社会偏好和策略互动提供了天然切入点。
3. Types of Economic Experiments | 经济实验的类型
Laboratory experiments take place in a fully controlled setting, often with monetary incentives and isolated subjects, allowing researchers to isolate causal mechanisms. Classroom experiments are a scaled‑down version, trading some degree of control for simplicity and immediate debriefing. Natural experiments exploit real‑world policy changes or external shocks as exogenous variation, while field experiments test hypotheses in natural environments with less awareness. For IB purposes, classroom‑based designs that mirror a single market or game are the most practical.
实验室实验在完全受控的环境中进行，通常提供货币激励并隔离被试，使研究者能分离因果机制。课堂实验是缩小版，用一定的控制度换取简洁性和即时小结。自然实验利用真实世界中的政策变化或外部冲击作为外生变异，而实地实验则在自然环境中以较低的觉察度检验假设。对IB而言，模拟单一市场或博弈的课堂设计最为实用。
4. Framing the Research Question and Hypotheses | 构建研究问题与假设
Start by identifying a clear economic concept you want to test — for instance, ‘Does a tax shift market incidence exactly as predicted by the elasticity rule?’ Formulate a null hypothesis (H₀) that states no difference or no relationship, and an alternative hypothesis (H₁) that reflects the theory’s prediction. For the tax example, H₁ could be: ‘Producers with less elastic supply bear a larger share of a per‑unit tax.’ Precise, directional hypotheses make your experiment easier to evaluate.
从明确你希望检验的经济概念入手——例如，“税收是否完全按照弹性规则转移市场负担？”构建一个陈述无差异或无关系的零假设（H₀），以及一个反映理论预测的备择假设（H₁）。就税收例子而言，H₁可为：“供给弹性较小的生产者承担了单位税负的更大份额。”准确且具有方向性的假设能使你的实验更容易评估。
5. Designing the Treatments and Variables | 设计处理组与变量
The independent variable is the treatment you deliberately change — for example, introducing a per‑unit subsidy in a market session. The dependent variable is the outcome you measure, such as the average price or total quantity traded. Control variables (number of buyers, identical cost structures, no communication) must be held constant to avoid confounding effects. Use a within‑subject design to let the same group experience both baseline and treatment, or a between‑subject design with separate groups. Keep the protocol as simple as possible: too many treatments dilute focus.
自变量是你有意改变的处理——例如，在市场场次中引入单位补贴。因变量是你测量的结果，比如平均价格或总交易量。控制变量（买家数量、相同的成本结构、禁止沟通）必须保持不变以避免混杂效应。采用被试内设计让同一组人先后经历基线和处理，或采用被试间设计使用不同小组。方案尽量简单：过多的处理会分散焦点。
6. Participants, Incentives and Ethics | 参与者、激励与伦理
Your classmates are the most accessible participant pool. Assign roles randomly — some as buyers with reservation values, others as sellers with costs. Provide a clear earnings formula, even if payoffs are points or sweets rather than real money, because salient incentives drive truthful revelation of preferences. Obtain informed consent, explain that participation is voluntary, and ensure anonymity of decisions. Debrief thoroughly: discuss the economic intuition behind observed outcomes and any discrepancies with theory.
你的同学是最便捷的参与者群体。随机分配角色——一些人作为有保留价值的买家，另一些作为有成本结构的卖家。提供一个清晰的收益公式，即使报酬是点数或糖果而非真钱，因为突出的激励能驱动真实偏好的显示。取得知情同意，说明参与是自愿的，并确保决策匿名。结束时充分小结：讨论观察结果背后的经济直觉以及与理论的任何偏差。
7. Procedures and Scripts | 实验流程与脚本
Prepare a script that states each period’s sequence, allowable actions, timing and how trades are executed. For a market experiment, you might use a spreadsheet where buyers and sellers submit quotes, or simply use paper slips in a double‑oral auction. Display a countdown timer and announce ‘the market is open.’ Run several periods to allow convergence. Record all transactions. Avoid guiding participants toward a ‘correct’ answer; your role is to facilitate, not to lead.
准备一份脚本，说明每个轮次的流程、允许的行动、时间安排以及交易执行方式。对于市场实验，可以使用电子表格让买卖双方提交报价，或仅在双口头拍卖中使用纸条。显示倒计时器并宣布“市场开放”。运行多个轮次以允许收敛。记录所有交易。避免引导参与者走向“正确”答案；你的角色是协助，而非领导。
8. Collecting Reliable Data | 收集可靠数据
Record the key metric for every transaction or decision: price, quantity, contribution amount, or offer made. Use a structured observation sheet or a simple polling app. Take a screenshot of the final supply‑and‑demand schedule if possible. Keep separate logs for each period to track dynamics. Immediately after the experiment, ask participants to fill in a brief anonymous questionnaire on their strategies and reasoning; this qualitative insight helps explain any anomalous behaviour.
记录每笔交易或决策的关键指标：价格、数量、贡献额或报价。使用结构化的观察表或简单的投票应用。如有可能，截取最终的供需表截图。为每个轮次单独记日志以追踪动态变化。实验结束后立即要求参与者填写一份关于其策略和推理的简短匿名问卷；这种定性洞察有助于解释任何反常行为。
9. Analysing Experimental Data | 分析实验数据
Begin with descriptive statistics: calculate the mean price per period and compare it with the theoretical equilibrium. Plot a time‑series chart to see convergence. For treatment comparisons, use a simple t‑test (even manual calculation) or a spreadsheet function to check if differences are statistically significant. Do not simply judge by eye. Report p‑values and effect sizes honestly. Remember, a finding of ‘no significant difference’ can be as informative as rejecting the null, especially in behavioural experiments.
从描述性统计入手：计算每个轮次的平均价格并与理论均衡比较。绘制时间序列图观察收敛情况。对于处理组比较，使用简单的t检验（甚至手工计算）或电子表格函数来检查差异是否具有统计显著性。不要仅凭肉眼判断。诚实地报告p值和效应量。记住，“无显著差异”的发现可能与拒绝零假设一样有价值，尤其是在行为实验中。
10. Connecting Results to IB Theory | 将结果与IB理论相联系
Use IB diagrammatic analysis to illustrate why outcomes aligned or diverged. Did a tax cause deadweight loss exactly as the Harberger triangle predicts? Did a public goods game exhibit free‑riding to the extent of the prisoner’s dilemma? Bring in concepts like marginal social benefit, Nash equilibrium, or anchoring from the behavioural syllabus. Highlight which assumptions of the model were violated in practice and why that matters. This synthesis is the core of an excellent IA commentary or extended essay.
运用IB图表分析来说明结果为何与理论一致或偏离。税收是否如哈伯格三角所预测那样造成了无谓损失？公共物品博弈是否显示了囚徒困境的程度？引入诸如边际社会收益、纳什均衡或行为大纲中的锚定效应等概念。指出模型的哪些假设在现实中遭到了违背及其原因。这种综合是优秀IA评论或拓展论文的核心。
11. Common Mistakes and How to Fix Them | 常见错误及补救方法
One frequent error is designing an experiment too complex to interpret; stick to testing one clear mechanism at a time. Another is forgetting to control communication between participants, which can lead to collusion and destroy internal validity. A third is insufficient sample size: if you have only six data points, variability will mask real effects. Run at least five trading periods and, if possible, replicate the experiment with another class. Finally, do not overclaim — state the limits of your design openly.
一个常见错误是实验设计过于复杂而难以解读；务必每次只检验一个清晰的机制。另一个错误是忘记控制参与者之间的沟通，这可能导致合谋并破坏内部效度。第三是样本量不足：若仅有六个数据点，变异性会掩盖真实效应。至少运行五个交易轮次，如有可能，在另一个班级重复实验。最后，不要过度声称——开诚布公地说明你设计的局限性。
12. From Experiment to IA and Beyond | 从实验到IA及更多
A well‑documented classroom experiment can become the foundation of an outstanding commentary. Extract a key microeconomic or macroeconomic concept — market failure, asymmetric information, externalities — and use your data as a concrete real‑world illustration, alongside a news article. The experiment trains you to critically assess policy simulations, which is an invaluable skill for Papers 1 and 2. Moreover, experiencing the behavioural twists firsthand makes you a more thoughtful economist, ready to question the assumptions behind every model you learn.
一次记录良好的课堂实验可以成为出色评论的基础。提取一个关键的微观或宏观经济概念——市场失灵、信息不对称、外部性——并将你的数据作为一个具体的真实世界例证，与新闻文章一同使用。实验训练你批判性地评估政策模拟，这是卷一和卷二极为宝贵的技能。此外，亲身经历行为偏差能让你成为更深思熟虑的经济学者，随时准备质疑你所学的每一个模型背后的假设。
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