本研究運用線性迴歸模型來預測微型金融對於貧窮、高中就讀率等等社會問題所帶來的效果，其中微型金融包括了微型信貸、微型儲蓄、微型保險以及微型金融機構所提供的匯款服務。本研究的樣本涵蓋了從2011年到2014年拉丁美洲及加勒比地區的20個國家。 在把樣本細分成可以比較的不同組別，並進行迴歸分析之後，我們發現微型金融對於貧窮人數有負向的顯著影響，對於高中就讀率有正向的顯著影響，而對於其他如醫療、創業、家庭支出與人均收入的影響並不顯著。 因應在拉丁美洲和加勒比地區不斷增加的微型金融機構，本研究建議未來可以利用更複雜的統計模型像是工具變量、隨機對照實驗、準實驗問卷來估計微型金融與影響之間是否有因果關係，對於NMP來說，他們應該鼓勵微型金融的發展以及接受適度的批判來確保透明且可靠的研究來作為政策制定的參考。 / The following research uses a panel linear model regression to detect possible effects Microfinance and its iterations (namely microcredit, microsavings, microinsurance, and remittance services offered by microfinancial institutions) have on distinct social outcomes such as poverty and secondary school enrollment rates. The study sample consists of 20 countries in the Latin American and Caribbean region observed during a period of 4 years (2011-2014). After subdividing the sample into comparable groups the results yielded statistically significant negative effects on poverty headcount, and statistically significant positive effects on secondary school enrollment rates across the subgroups. The results from other social welfare dimensions such as health, business creation, household consumption, and income per capita were insignificant. Due to the increasing presence of Microfinancial institutions in Latin America and the Caribbean, there is sufficient reason to encourage further research to be done in which more experienced researchers can use more statistically complex models (such as IV, RCTs, quasi-experimental surveys) to try to determine whether or not there is a causal relationship between microfinance and the effects herein described. For policymakers and funders of NMPs, the takeaway is that they should encourage both advocates and critics to present transparent and replicable studies to back their claims.

本論文共分三章，全數圍繞在消費尤拉方程式中，消費成長的高階動差在理論與實證上的重要性。分別說明如下： 本論文第一章討論消費高階動差在實證估計消費結構性參數之重要性。消費尤拉方程式是消費者極大化問題的一階條件，而自Hall (1978)起，估計消費結構參數如跨期替代彈性時，也多是利用這個尤拉方程式所隱涵的消費動態關係，進行估計。但是由於消費資料存在嚴重的衡量誤差問題，實證上多將尤拉方程式進行對數線性化，或是二階線性化後進行估計。 然而前述一、二階線性化，固然處理了資料的衡量誤差問題，卻也造成了參數估計上的近似誤差(approximation bias)。其原因來自於線性化過程中所忽略的高階動差實為內生，而與迴歸式中的二階動差相關。這使得即便用工具變數進行估計，仍然無法產生具有一致性的估計結果。這當中的原因在於足以解釋二階動差，卻又與殘差項中的高階動差直交的良好(valid)的工具變數無法取得。 我們認為在資料普遍存在衡量誤差的情況下，線性化估計尤拉方程式不失為一可行又易於操作的方法。於是我們嘗試在線性化的尤拉方程式中，將高階動差引入，並檢視這種高階近似是否能有效降低近似誤差。我們的模擬結果首先證實，過去二階近似尤拉方程式的估計，確實存在嚴重近似誤差。利用工具變數雖然可以少部份降低該誤差，但由於高階動差的內生性質，誤差仍然顯著。我們也發現，將高階動差引入模型，確實可以大幅降低近似誤差，但是在偏誤降低的同時，參數估計效率卻也隨之降低。 高階動差的引入，除了降低近似偏誤外，卻也必須付出估計效率降低的代價。我們因此並不建議無限制地放入高階動差。則近似階次選取，乃為攸關估計績效的重要因素。本章的第二部份，即著眼於該最適近似階次選取。我們首先定義使參數估計均方誤(mean squared error, MSE)為最小的近似階次，為最適近似階次。我們發現，該最適階次與樣本大小、效用函數的彎曲程度都有直接的關係。 然而在實際進行估計時，由於參數真值無法得知，MSE準則自然無法作為階次選取之依據。我們於是利用目前在模型與階次選取上經常被使用的一些準則進行階次選取，並比較這些不同準則下參數估計的MSE。我們發現利用這些準則，確實可以使高階近似尤拉方程式得到MSE遠低於目前被普遍採用的二階近似的估計結果，而為估計消費結構參數時更佳的選擇。 本論文第二章延續前一章的模擬結果，嘗試利用消費高階動差間的非線性關係，進一步改善高階近似消費尤拉方程式的估計表現。由第一章的研究結果，我們發現高階近似估計確有助大幅降低近似誤差，但這其中可能產生的估計效率喪失，卻是輕乎不得的。這個效率喪失，很大一部份來自於我們所使用的工具變數，雖然可以有效掌握消費成長二階動差的變動，但是當這同一組工具變數被用來解釋如偏態與峰態等這些更高階動差時，預測力卻大幅滑落。這使待得當我們將這些配適度偏低的配適後高階動差，放到迴歸式中進行估計時，所能提供的額外情報也就相當有限。而所造成的共線性問題，也自然使得估計效率大幅惡化。 於是在其他合格的工具變數相對有限的情況下，我們利用高階動差間所存在的均衡關係，將原來的工具變數進行非線性轉換，以求得對高階動差的較佳配適。由於消費動差間之關係，尚未見諸相關文獻。於是我們首先透過數值分析，進一步釐清消費高階動差間之關係。這其中尤為重要的是由消費二階動差所衡量的消費風險，與更高階動差間之關係。因為這些關係將為我們轉換工具變數之依據。 我們發現與二階動差相一致地，消費者對這些高階動差之預期，都隨其財富水準的提高而減少。這隱涵消費風險與更高階動差間之正向關係。更進一步檢視消費風險與高階動差間之關係也發現，二者間確實存在非線性之正向關係。而這也解釋了何以前一章線性的工具變數，雖可適切捕捉消費風險，但對高階動差的解釋力卻異常薄弱。 利用這些非線性關係，我們將原始的工具變數進行非線性轉換後，用以配適更高階動差。透過模擬分析，我們證實了這些非線性工具變數，確實大幅改善高階近似尤拉方程式的估計表現。除了仍保有與線性工具變數般的一些特性，諸如隨樣本的增加，最適近似階次也隨之增加之外，相較於線性工具變數，非線性工具變數可以在較低的近似階次下，就使得估計偏誤大幅下降。在近似階次愈高估計效率愈低的情況下，這自然大幅度地提高了估計效率。比較兩種工具變數估計結構數參數所產生的MSE也證實，非線性工具變數確實有遠低於原始線性工具變數的MSE表現。 然而我們同時也發現，利用非線性工具變數估計，若未適當選擇近似階次，效率喪失的速度，可能更甚於線性工具變數時。這凸顯了選擇近似階次的重要性。於是我們同樣檢視了前述階次選擇準則在目前非線性工具變數環境下的適用性。而總結第一、二章的研究結果，我們凸顯了高階動差的重要性，確實助益重要消費結構參數估計。而利用過去尚未被討論過的高階動差間非線性關係，更可大幅度改善估計績效。 本論文的最後一章，則旨在理論上建立高階動差的重要性。我們在二次式的效用函數(quadratic utility function)設定下，推導借貸限制下的最適消費決策。二次式的效用函數，由於其邊際價值函數(marginal value function)為一線性函數，因此所隱涵的消費決策，具有確定相等(certainty equivalence)的特性。這表示消費者只關心未來的期望消費水準，二階以上的更高階動差，都不影響其消費決策。然而這種確定相等的特性，將因為借貸限制的存在而不復存在，而高階動差的重要性也就因此凸顯。 我們證明，確定相等特性的喪失，其背後的理論原因在於，借貸限制的存在，使得二次式效用函數的邊際價值函數，產生凸性。消費者因而因應未來的不確定性，進行預防性儲蓄。透過分析解的求得，我們也得以進一步分析更高階動差的對消費決策的理論性質。同時我們也引申理論推導的實證意涵，其中較重要者諸如未受限消費者因預防性儲蓄行為所引發的消費過度敏感性現象，實證上樣本分割法的選取，以及高階動差的引入模型。 / The theme of this thesis seeks to explore the importance of higher-order moments in the consumption Euler equation, both theoretically and empirically. Applying log-linearized versions of Euler equations has been a dominant approach to obtaining sensible analytical solutions, and a popular choice of model specifications for estimation. The literature however by now has been no lack of conflicting empirical results that are attributed to the use of the specific version of Euler equations. Important yet natural questions whether the higher-order moments can be safely ignored, or whether higher-order approximations offer explanations to the stylized facts remain unanswered. Such inquires as in the thesis thus can improve our understanding toward consumer behaviors over prior studies based on the linear approximation. 1. What Do We Gain from Estimating Euler Equations with Higher-Order Approximations? Despite the importance of estimating structural parameters governing consumption dynamics, such as the elasticity of intertemporal substitution, empirical attempts to unveil these parameters using a log-linearized version of the Euler equation have produced many puzzling results. Some studies show that the approximation bias may well constitute a compelling explanation. Even so, the approximation technique continues to be useful and convenient in estimation of the parameters, because noisy consumption data renders a full-fledged GMM estimation unreliable. Motivated by its potential success in reducing the bias, we investigate the economic significance and empirical relevance of higher-order approximations to the Euler equation with simulation methodology. The higher-order approximations suggest a linear relationship between expected consumption growth and its higher-order moments. Our simulation results clearly reveal that the approximation bias can be significantly reduced when the higher-order moments are introduced into estimation, but at the cost of efficiency loss. It therefore documents a clear tradeoff between approximation bias reduction and efficiency loss in the consumption growth regression when higher-order approximations to the Euler equation is considered. A question of immediate practical interest arises ``How many higher-order terms are needed?'' The second part of our Monte-Carlo studies then deals with this issue. We judge whether a particular consumption moment should be included in the regression by the criterion of mean squared errors (MSE) that accounts for a trade-off between estimation bias and efficiency loss. The included moments leading to smaller MSE are regarded as ones to be needed. We also investigate the usefulness of the model and/or moment selection criteria in providing guidance in selecting the approximation order. We find that improvements over the second-order approximated Euler equation can always be achieved simply by allowing for the higher-order moments in the consumption regression, with the approximation order selected by these criteria. 2. Uncovering Preference Parameters with the Utilization of Relations between Higher-Order Consumption Moments Our previous attempt to deliver more desirable estimation performance with higher-order approximations to the consumption Euler equation reveals that the approximation bias can be significantly reduced when the higher-order moments are introduced into estimation, but at the cost of efficiency loss. The latter results from the difficulty in identifying independent variation in the higher-order moments by sets of linear instruments used to identify that in variability in consumption growth, mainly consisting of individual-specific characteristics. Thus, one major challenge in the study is how to obtain quality instruments that are capable of doing so. With the numerical analysis technique, we first establish the nonlinear equilibrium relation between consumption risk and higher-order consumption moments. This nonlinear relation is then utilized to form quality instruments that can better capture variations in higher-order moments. A novelty of this chapter lies in adopting a set of nonlinear instruments that is to cope with this issue. They are very simple moment transformations of the characteristic-related instruments, thereby easy to obtain in practice. As expected, our simulations demonstrate that for a comparable amount of the bias corrected, applying the nonlinear instruments does entail an inclusion of fewer higher-order moments in estimation. A smaller simulated MSE that reveals the improvement over our previous estimation results can thus be achieved.\ 3. Precautionary Saving and Consumption with Borrowing Constraint This last chapter offers a theoretical underpinning for the importance of the higher-order moments in a simple environment where economic agents have a quadratic-utility preference. The resulting Euler equation gives rise to a linear policy function in essence, or a random-walk consumption rule. The twist in our theory comes from a presence of borrowing constraint facing consumers. The analysis shows that the presence of the constraint induces precautionary motives for saving as responses from consumers to income uncertainties, even there has been no such motives inherent in consumers' preference. The corresponding value function now displays a convexity property that is virtually only associated with more general preferences than a quadratic utility. The analytical framework allows us to be able to characterize saving behaviors that are of precautionary motives, and their responses to changes in different moments of income process. As empirical implications, our analysis shed new light on the causes of excess sensitivity, the consequences of sample splitting between the rich and the poor, as well as the relevance of the higher-order moments to consumption dynamics, specifically skewness and kurtosis.

連續時間計量方法在國外已廣泛被使用於經濟理論的實證上，而國內相關的研究猶付之如闕。本文首先簡述連續時聞計量方法的緣起及其優點；接著介紹其研究方法；最後以此法對耐久財需求、非自願儲蓄及匯率的決定三個主題進行研究。 　　本文第四章透過消費者耐久財的需求發現，以RMSE為準則時，連續模型所賦予的結構訊息是否優於離散模型，須視經濟現象本身的性質而定。 　　有關第五章台灣地區非自願儲蓄之研究，其結論可歸納為：即使考慮不同預期行為，Deaton (1977) 所宣稱的非自願儲蓄效果仍不顯著。但隨著產品行銷管道日漸流通等因素，此一效果亦值得有關當局注意。 　　第六章中筆者修改Frankel & Rodrignez (1982) 之模型，並利用逼近法進行估計。在完全預期的假設下，可以發現模型配適的匯率波動幅度遠大於實際匯率走向。而考慮政府干預後，模型配適情況良好。最後，就樣本後預測準則而言，本章所考慮之模型皆優於VARX(1,2)。

本論文題旨為：「論代間正義：一個羅爾斯式的觀點」。代間正義是晚近三十年來新興且益愈受到重視的倫理學議題之一，其主要關切的核心問題，乃在於追問「當代之於後代所應擔負的責任」。本文透過當代政治哲學與倫理學家羅爾斯（John Rawls）有關社會正義理論的設計與主張，分兩部分處理此問題。 / 第一部份所處理的問題為由帕菲特（Derek Parfit）所深化之「後代人格不同一問題」（The Non-Identity Problem），旨在探究「代間正義是否可能」。帕菲特指出，前代不同的行為選擇，將造成不同後代的存在，而這使得現存既有之各種權利與責任相對應的理論，無法合理地適用於代間關係。帕菲特主張，可以採取「忽略特定人格的比較（品質）原則」以解決此後代人格不同一問題。然而，帕菲特此舉卻陷入「不特定人格的後代無法追究前代之行為責任」的理論困境。本文主張，透過羅爾斯原初位置（original position）的理論設計啟發，即便在代間存在著「前代不同的行為選擇，將造成不同後代的存在」的後代人格不同一疑慮，當代仍可採納原初位置的理論啟示，區分人的屬性（properties）與獨特性（particular）的差異，在後代存有人格不同一問題（獨特性）的情形下，針對「屬性」而確立追問當代之於後代所應擔負責任之正當性。 / 第二部分主要處理羅爾斯有關代間正義觀點的內部論證問題，並進一步藉此說明「代間正義如何可能」。羅爾斯以「正義的儲蓄原則」（just savings principle）說明代間的分配正義問題，並《正義論》（A Theory of Justice）中將它納入正義二原則之中，成為建構社會基本體制的基本原則之一。然而，羅爾斯早期解釋與證成儲蓄原則的相關理據如動機假定（motivation assumption）與家族模式等，卻可能與其他理論假定如締約者的理性等相衝突、衍生解釋融貫上的困難，而遭到眾多學者們的質疑。羅爾斯在一九九三年的《政治自由主義》（Political Liberalism）中對此做出回應，並將關切下一代的動機假定，修正為「要求前代也承諾遵守他們所遵守的儲蓄原則，無論向前或向後追溯多遠」。除此之外，羅爾斯於《正義論》以外的其他著作，在提及正義二原則時，皆不再表述「正義的儲蓄原則」。本文認為羅爾斯後期所提出的證立主張，不僅整合了代內分配正義（差異原則）與代間分配正義（儲蓄原則）的論證理據（小中取大規則的應用），更與其主張「社會作為一世代相繼之公平的合作體系」時所標舉之「相互性理念」（the idea of reciprocity）的核心概念相符應。本文認為，在論證理據得到順利整合的前提下，羅爾斯仍可在後期表述正義二原則時，將「正義的儲蓄原則」放回其中，並可據此呼應當代永續發展理念「既滿足當代人的需求，又不對後代人滿足其需求的能力造成危害」的核心主張。 / The topic “Intergenerational Justice” is one of the newest but getting more important ethics problems to contemporaries. One of the key points of this issue is how to make sense of our obligations to the posterity (include future people) if possible. In this dissertation, I intend to clarify this problem by Rawls’s theory of justice into two parts. / The first part is “The Non-Identity Problem” held by Derek Parfit. This problem shows that “in the different outcomes, different people would be born”, and it seems inactive the traditional theories of rights. Parfit suggests that we can through it by the priinciple Q: “if in either of two outcomes the same number of people would ever live, it would be bad if those who live are worse off, or have a lower quality of life, than those who would have lived.” But this principle makes new difficulties about this problem. According Reiman, I argue that we can adjust this non-identity problem by the theory hypothesis “Original Position” of Rawls’s theory of justice, and that there are obligations from contemporaries to the future people. / The second part is about the arguments of Rawls’s theory of justice between generations. According to early Rawls in 1971, the theory of justice between generations represented by the “just savings principle” and was one part of the Two Principles of Justice in A Theory of Justice. But there are some argument troubles about the assumptions that makes the theory of justice between generations difficultly, especially on the “motivation assumption” and the family mode and so on. In 1993, Rawls changed his arguments about the theory of justice between generations, but he also take off the just savings principle from the Two Principles of Justice in other books or articles besides A Theory of Justice. I argue that latter arguments seem more reasonable to the theory of justice between generations, and they also makes the whole theory of social justice comprehensive. Then I argue that Rawls can still presents the just savings principle when he says about the Two Principles of Justice.

本研究建構一社會網路互動下的新凱因斯動態隨機一般均衡模型，探討效用基礎下波茲曼分配背後的網路結構，以及，社會網路對新凱因斯動態隨機一般均衡模型參數的影響。根據本論文模擬結果，效用基礎下波茲曼分配背後所隱含的社會網路結構呈現局部區域性連結拓璞，此結論與熱力學對波茲曼分配中粒子互動方式的假設相同，然而，區域性連結之網路結構（如環狀網）並非目前實證研究所觀察到的網路型態（如冪分布網路或高群集係數之小世界網路），故吾人是否得以直接利用效用基礎下波茲曼分配來描述社會上人與人之間的互動現象必需更忱慎考量之。另外，社會網路互動也將使新凱因斯動態隨機一般均衡模型之參數估計產生偏誤，依本研究估計結果觀之，只要加入社會互動，總合需求曲線中實質利率之參數估計將為正號，即實質利率對產出缺口的影響為負向影響，也就是文獻上的投資儲蓄迷思(IS puzzle)，若進一步觀察社會網路結構對該實證迷思的影響則可發現當社會網路群聚程度越高時，該估計偏誤將越嚴重。 / We construct a social network-based New Keynesian DSGE (Dynamic Stochastic General Equilibrium) Model to investigate the underlying social network structure derived from the performance-based Boltzmann-Gibbs model, and thus interpret the process that social network structures affect the estimation bias in the New Keynesian DSGE framework. According to our simulation results, the underlying social network structure derived from the performance-based Boltzmann-Gibbs model should be local. This finding is consistent with the study of thermodynamics, which the Boltzmann-Gibbs distribution is based upon, i.e. the local interaction. However, it contradicts not only the purpose of combining the performance-based Boltzmann-Gibbs machine and New Keynesian DSGE model, but also empirical studies of social network structures in the real world. Accordingly, maybe we have to consider further whether the performance-based Boltzmann-Gibbs machine is a suitable tool for calibrating social interaction under the stylized New Keynesian DSGE framework. Furthermore, if we embedded interaction behavior in the stylized New Keynesian model, the so-called “IS Puzzle” can be consequently observed. We also realized that “IS Puzzle” is connected with network structures. The more clustering the network structure is, the more significant “IS Puzzle” would be.