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**A**: (2018). Additionally, we offer a theory-driven approach for choosing the penalization level for the lasso estimation steps, eliminating the need for computationally intense cross-validation procedures. Similar to Gregory et al. (2021), Lu et al. (2020) assume normally distributed errors that are independent of X𝑋Xitalic_X**B**: In contrast, our model framework allows us to dispense with the normality assumption and only requires the existence of the fourth moment of the error term. Moreover, our main results are also compatible with a heteroskedastic error. Additionally, we can overcome the requirement outlined in Lu et al. (2020) that the number of relevant regressors is bounded. Instead, our model allows the number of relevant regressors to grow to infinity with increasing sample size.**C**: The advantage of our proposed estimator is that we do not have to leave the sieves framework while establishing the uniform validity of the resulting confidence bands. Interestingly, Lu et al. (2020) conclude that ”it is challenging to study the uniform confidence
band through pure sieve-type approaches” (p. 4). However, this is exactly our main contribution: achieving uniform inference within a sieve framework. We accomplish this by framing the problem as one of high-dimensional Z-estimation, utilizing recent results from Belloni et al | ACB | BCA | ACB | CBA | Selection 2 |
**A**:
The structure of the work is the following: in Sec**B**: 2 we provide an extension to the theory and we define a new set of Finite Change Sensitivity Indices (FCSIs) for functional-valued responses, while in Sec**C**: 3 we then proceed to present and develop the methodology to assess the uncertainty associated with these FCSIs. | BCA | BAC | ACB | ABC | Selection 4 |
**A**: Excludability is a joint condition on
preferences and information**B**: It requires that for any pair of actions, a single agent can become arbitrarily certain that one action is strictly better than the other, starting from any belief that does not exclude that event**C**: Since excludability is defined using preferred sets, it is straightforward to deduce which sets must be distinguishable for any given preferences; Lemma 1 then provides a set of likelihood-ratio conditions on the information structure, without reference to beliefs. | ABC | ACB | BCA | BCA | Selection 1 |
**A**: That said, it can also be extended in several directions which either preserve the main results or generate interesting new ones**B**: We briefly review here the main assumptions and related extensions, the details of which are for the most part in the Appendix.**C**:
Like any economic model, the one above is a stylized representation of a more complex reality that aims to capture essential features in order to build insight | BCA | CAB | ACB | ABC | Selection 1 |
**A**: IR, PE, NB, On, An, ESP, PaE, SP, TI, and TP respectively refer to individual rationality, Pareto efficiency, non-bossiness, ontoness, anonymous, endowments-swapping-proofness, pair-efficiency, strategy-proofness, truncation-invariance and truncation-proofness.
**B**: The notation τ𝜏\tauitalic_τ stands for the TTC rule, and NT stands for the no-trade rule where each agent is assigned his/her endowment**C**: The notation “✓✓\checkmark✓” in a cell means that the axiom is satisfied in the corresponding literature | BAC | CBA | BCA | CAB | Selection 2 |
**A**:
We are interested in regression models for ordinal outcomes that allow for lagged dependent variables as well as fixed effects**B**: We study identification and estimation of the finite-dimensional parameters in this model when only a small number (≥4absent4\geq 4≥ 4) of time periods is available.**C**: In the model that we propose, the ordered outcome depends on a fixed effect, a lagged dependent variable, regressors, and a logistic error term | BAC | CAB | ACB | CBA | Selection 3 |
**A**: We make use of conditional independence tests based on kernel mean embeddings, i.e., maps of probability distributions into reproducing kernel Hilbert spaces (RKHS) \parencite[see][for a survey]muandetetal16kernel. Intuitively, this corresponds to approximating conditional distributions with unconditional ones by weighting with an appropriate kernel, and evaluating their covariance in an RKHS.**B**: Specifically, we show that identification of the causal direction is equivalent to a conditional independence test of covariates and error terms given control variables**C**:
Following [hoyer09anm], we also demonstrate how our testability result can be applied in empirical practice | ACB | BAC | BCA | CBA | Selection 4 |
**A**: These factors should have been present in Britain but absent in China.**B**: The figure shows that Britain’s GDP per capita was similar to that of China before 1750, but diverged after that.
To understand why the Industrial Revolution occurred in Britain in the 18th century, researchers need to identify factors that caused what he refers to as the Great Divergence–the divergence in economic growth between Europe and China since the 19th century**C**: This claim is supported by recent estimates of GDP per capita, as plotted in Figure 1 | BCA | CAB | CAB | CBA | Selection 4 |
**A**: Because there are only three trust questions, the first principal component summarizes most of the information from the trust questionnaire. It places positive weight on the question that involves trust and negative weights on two questions that suggest mistrust. Perhaps surprisingly, this measure of trust is associated with a positive interaction on contribution costs in the baseline, which indicates that individuals who score highly on trust are less altruistic and more careful about where they direct effort in the baseline**B**: This suggests that these individuals are trustworthy in that they respond to sharing by others by increasing their own contribution. However, they are less likely to share blindly and trust that others will reciprocate. In the treatment, estimates of the effect of trust are less precise but suggest a reversal of this phenomenon; they trust that others will reciprocate when they know that others will be aware of their sharing behavior. This is captured by the negative estimate of the interaction between trust, the treatment indicator, and contribution costs, together with the positive estimate of the coefficient for the interaction between trust, the treatment indicator, and direct reciprocity. This sheds more light on information as a mechanism driving the mixed results regarding trust and sharing behavior in public goods games, observed in previous work (Anderson et al., 2004).
**C**: This agrees with the results of Glaeser et al. (2000), which suggest that such trust questionnaires predict trustworthy behavior but do not necessarily predict trusting behavior. Further in line with these results is a strong positive interaction of the trust characteristic with generalized reciprocity in the baseline | CAB | CAB | ACB | ABC | Selection 3 |
**A**: The hybrid methods cALS and cOALS improve the original randomized initialized ALS and OALS significantly, showing the advantages of the cPCA initialization**B**: It is worth noting that cOALS has comparable performance with 1HOPE and HOPE when δ𝛿\deltaitalic_δ is small.
**C**: In addition, ALS and cALS are always the worst under the cases δ≥0.1𝛿0.1\delta\geq 0.1italic_δ ≥ 0.1 | CBA | BAC | ABC | BCA | Selection 4 |
**A**: Theorem 2 shows that for choice rules defined on ordered type spaces, it is without loss for such a designer to consider only bimonotonic protocols**B**: Formally, the result is a representation theorem, showing that every protocol is contextual privacy equivalent to a bimonotonic protocol. A bimonotonic protocol consists of threshold queries which, for each agent, are monotonically increasing or decreasing in the threshold.
**C**: To get to these insights, we first present a key theoretical result of the paper that helps us reason about the contextual privacy-implementation frontier | BCA | BAC | CBA | BAC | Selection 1 |
**A**: The relationship between Stokes’ theorem and these results is also discussed.
**B**: Finally, the study discussed in section 3.2 is related to section 4 of Osana (1992)**C**: This paper, written in Japanese, discusses not only consumer surplus but also the relationship between this and equivalent and compensating variations | CAB | BAC | BCA | ACB | Selection 1 |
**A**: Almost surely either a player was chosen on Step 1 or 2 or the sum of just the odd-numbered terms (given by B’s moves) of expression (2) diverges to ∞\infty∞, by Lemma 3.6**B**: In the latter case, the sum of the even-numbered terms must diverge to −∞-\infty- ∞ (as the sum of all terms is convergent), and therefore cannot diverge to ∞\infty∞**C**: Thus player B is chosen on this step with probability 00, finishing the proof.
∎ | BAC | BCA | BCA | ABC | Selection 4 |
**A**: Hence, for example, it is quite easy to derive the convergence result in the closed convergence topology from Theorems 2-3. In this connection, in econometric studies that use statistical models that require a particular shape for the utility function, we can inversely derive the compact convergence of their utility function from the convergence of corresponding orders in the closed convergence topology. In this sense, the use of a specified shape of the utility function is not a disadvantage for Theorems 2-3.
**B**: If the shapes of utility functions are specified for some set of weak orders, then in most cases, the compact convergence of the utility function is equivalent to the convergence in the closed convergence topology of the weak order**C**: As a final note, we mention the closed convergence topology of weak orders | CAB | CBA | CAB | ACB | Selection 2 |
**A**: Individuals are weighted in the social evaluation according to their rank in the distribution**B**: To define and formalize this statement, start with the case of a single attribute. Weymark (1981) shows that social evaluations that satisfy the comonotonic independence property defined below take the form of weighted sums of quantiles.**C**:
Next, and more substantively, all social evaluation functionals that are compatible with the Lorenz dominance criterion are rank-dependent social evaluation functionals | CBA | CAB | BAC | BCA | Selection 4 |
**A**: These works model the interaction between a predictor and its environment (strategic agents), and develop methods that are robust to the distribution shift induced by the predictor**B**: However, a key distinction between our work and these references is that we optimize decisions by explicitly considering utility from treatment assignment with strategic agents,**C**:
Our work is also related to strategic classification (Ahmadi et al., 2022; Brückner et al., 2012; Chen et al., 2020; Dalvi et al., 2004; Dong et al., 2018; Hardt et al., 2016; Jagadeesan et al., 2021; Kleinberg and Raghavan, 2020; Levanon and Rosenfeld, 2022) and performative prediction (Miller et al., 2021; Perdomo et al., 2020) | CBA | BAC | ABC | BCA | Selection 4 |
**A**: While the treatment and control group affected approximately the same number of facilities, the number of treated and control patients are very different due to the unequal number of patients across facilities. Figure 3 provides a histogram of the number of patients attending each clinic for their first prenatal visit during the intervention period. This distribution has a mean and a standard deviation of 33.6 and 16.3 patients per clinic, respectively. Finally, the post-intervention period goes between January 2011 and March 2012.**B**: During this period, the sample average of the week of the first prenatal visit is 16.97, and only 34.46% of these visits occur before week 13. Figure 2 shows a histogram of this distribution. The aforementioned treatment occurred exclusively during the intervention period, which ran between May 2010 and December 2010**C**:
Celhay et al. (2019) collected data before, during, and after the intervention period. The pre-intervention ran between January 2009 and April 2010 | BAC | BAC | CBA | ABC | Selection 3 |
**A**: However, it is restricted by a constant and known demand rate as well as an infinite shelf life of SKUs. On the other hand, the newsvendor model states the classical inventory management model to determine the cost-optimal inventory level in case of stochastic customer demand (Silver et al.,, 1998, Zipkin,, 2000). Again, restrictive assumptions have to be accepted: In its basic version, the model considers independent demand periods, i.e. a shelf life of one demand period only.
**B**: The two basic models, both associated with very limiting assumptions, are the EOQ model and the newsvendor model**C**: Back in 1913, the EOQ model was the first to provide decision support for companies when it comes to the question of replenishment order quantities (Erlenkotter,, 1990) and still forms the basis for more recent approaches (see e.g. Alinovi et al.,, 2012) | CBA | ACB | BAC | CAB | Selection 4 |
**A**:
Under the minimum approach, the power curves of the CSUB and CS2B tests are very similar, suggesting that the power of the CS2B test comes mainly from using upper bounds**B**: This finding demonstrates the importance of exploiting upper bounds in addition to monotonicity and continuity restrictions in practice**C**: Figure 11 further shows that the power of the CSUB and the CS2B test may not be monotonic over h∈{0,1,2}ℎ012h\in\{0,1,2\}italic_h ∈ { 0 , 1 , 2 }. On the one hand, for large hℎhitalic_h, there are more p𝑝pitalic_p-values close to zero, where the upper bounds are more difficult to violate. On the other hand, the effective sample size increases with hℎhitalic_h, leading to more power. | ABC | CBA | BCA | ACB | Selection 1 |
**A**:
CO2 emissions (thousand metric tons of CO2): Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement**B**: They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring**C**: Source: World Bank WDI. | ABC | BAC | BCA | CBA | Selection 1 |
**A**: But, unlike many common estimators, SyNBEATS is not guaranteed to be consistent; it could be that its performance gains in terms of RMSE stem from providing concentrated, but potentially biased estimates. We explore each of these possibilities in turn.
**B**: SyNBEATS differs from other estimators in two important ways: (1) its use of both horizontal and vertical information to inform its imputation, and (2) its use of the N-BEATS residual block architecture**C**: In this section, we investigate the source of SyNBEATS’ strong observed performance relative to alternative estimators | CBA | BCA | CAB | ABC | Selection 1 |
**A**: Although the variance of the estimators with burn-in periods increases, the decrease in bias still results in a large decrease in the overall mean squared error. Furthermore, including burn-in periods leads to more accurate inferential results, with confidence intervals having coverage close to the nominal level. Again, we observe that the performance of the estimators with burn-in periods remains relatively stable regardless of the chosen length of the burn-in period.
**B**: As expected, we notice that the use of burn-in periods considerably reduces the bias of the treatment effect estimation**C**: Table 2 presents the bias, variance, mean squared error, and coverage achieved by those estimators | CAB | BCA | CBA | ACB | Selection 3 |
**A**: This severely limits the applicability of existing post-selection inference methods which are typically designed for (relatively) low-dimensional parameters of interest that can be estimated directly. Indeed, to our knowledge, impulse response analysis in sparse HD-SVARs is only considered in Krampe et al. (2022), who construct a complex multi-step algorithm to overcome these complications. Instead, by casting the problem in the LP framework, we reduce the impulse response parameter(s) to a (directly estimable) low-dimensional object in the presence of high-dimensional nuisance parameters, which makes the standard post-selection tools available.**B**:
While several methods and theoretical results now exist for estimating sparse VAR models – see e.g., Basu and Michailidis (2015); Kock and Callot (2015); Masini et al. (2022) and the references cited therein – inference on impulse responses is complicated by two issues**C**: First, sparse estimation techniques such as the lasso perform model selection, which induces issues with non-uniformity of limit results if this selection is ignored (Leeb and Pötscher, 2005). Second, while several methods such as orthogonalization (Belloni et al., 2014) and debiasing, or desparsifying the lasso (van de Geer et al., 2014; Javanmard and Montanari, 2014) have been proposed to yield uniformly valid (or ‘honest’) post-selection inference, the impulse response parameters are nonlinear functions of all estimated VAR parameters | BAC | ACB | CAB | BCA | Selection 3 |
**A**: Note that axes are not normalized**B**:
Figure 4: Prolific.co Worker Responses to prompts including reference to minimum wage ranging from $0 to $100**C**: The horizontal axis shows the value of the anchor, and the vertical axis the percentage of responses to that anchor. For high anchors, the distribution splits into two distinct modes (Fig. 2). | ABC | ABC | ABC | BAC | Selection 4 |
**A**: Without any such additional information, it does not seem clear whether we should call with the lower bound probability, upper bound probability, or a value in the middle of the interval. The point of the equilibrium refinements we have considered is exactly to help us select between equilibria in a theoretically principled way in the absence of any additional information that could be used to model the specific opponents.
**B**: The first argument seems much more natural than the second, as it seems much more reasonable that a human is aware they should check sometimes with weak hands, but may have trouble computing that n𝑛nitalic_n is the optimal size and guess that it is x.𝑥x.italic_x . However, both arguments could be appropriate depending on assumptions about the reasoning process of the opponent**C**: The entire point of Nash equilibrium as a prescriptive solution concept is that we do not have any additional information about the players’ reasoning process, so will opt to assume that all players are fully rational. If any additional information is available—such as historical data (either from our specific opponents’ play or from a larger population of players), observations of play from the current match, a prior distribution, or any other model of the reasoning mechanism of the opponents—then we should clearly utilize this information and not simply follow a Nash equilibrium | ACB | CAB | ABC | ACB | Selection 2 |
**A**: If the receiver could, then it would set an environment with prohibitively high misreporting costs to spur truthful reporting. However, organizations may be limited when choosing among mechanisms, either because of exogenous constraints or commitment problems. The main result is positive: efficiency can be obtained even when organizations can only decide how to structure communication.**B**: Even if the receiver could affect the senders’ payoff structure within the limits prescribed in Section 3, the only way to obtain an efficient and collusion-proof outcome is by using public advocacy**C**:
In the model, the receiver cannot implement transfers or choose the senders’ payoff structure.171717Mechanisms that involve transfers are inefficient because, compared to the outcome under complete information, at least one player incurs a cost when participating in a transfer | BAC | ACB | ACB | CBA | Selection 4 |
**A**: is empty**B**: The proof of Theorem 1 in MP is as follows**C**: First, any value
β𝛽\betaitalic_β consistent with the model lies in ℬγ(𝜹)subscriptℬ𝛾𝜹\mathcal{B}_{\gamma}\left(\boldsymbol{\delta}\right)caligraphic_B start_POSTSUBSCRIPT italic_γ end_POSTSUBSCRIPT ( bold_italic_δ ), | BAC | ACB | CBA | ABC | Selection 4 |
**A**: One approach to address this issue would be to use a binomial pricing tree (Shin, 2003) to determine the change in the firm’s value following multiple announcements.**B**: The difficulty lies in determining the change in a firm’s market value in response to each announcement when there are multiple announcements on any given day**C**:
Third, in this paper, we focused only on single announcements and ignored days with more than one announcement | CAB | BCA | CBA | ACB | Selection 3 |
**A**:
We will show that this complexity is high for 𝖳𝖳𝖢𝖳𝖳𝖢{{\mathsf{TTC}}}sansserif_TTC, providing another novel way in which 𝖳𝖳𝖢𝖳𝖳𝖢{{\mathsf{TTC}}}sansserif_TTC is complex**B**: In contrast, for 𝖣𝖠𝖣𝖠\mathsf{DA}sansserif_DA we give a new structural characterization which shows that this complexity is low in stable matching mechanisms**C**: In Section 4.3, we use this result to give additional characterizations and connections to [GHT23], illustrating how this result may be of independent interest. | ABC | CBA | CBA | BAC | Selection 1 |
**A**: There is**B**: i𝑖iitalic_i votes at all q′(i)>q(i)superscript𝑞′𝑖𝑞𝑖q^{\prime}(i)>q(i)italic_q start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT ( italic_i ) > italic_q ( italic_i ))**C**: As we document in the Appendix,
individual behavior in the experiment is mostly monotonic | BAC | CAB | CBA | BCA | Selection 2 |
**A**: Such abstraction is useful because it allows the outcomes of the model to be entirely attributed to the spatial mechanism of knowledge spillovers (as proposed by Bond-Smith, (2021))**B**:
Finally, we reiterate that the modeling of the innovation sector in this paper purposefully abstracts from the dynamic processes that usually drive innovation and the creation and diffusion of knowledge**C**: However, we argue that this mechanism could be extended to models of Schumpeterian growth, where the explicit modelling of innovation dynamics would allow to infer about an eventual circular causality between regional growth and agglomeration patterns (Baldwin and Martin,, 2004). | BAC | ABC | ACB | ACB | Selection 1 |
**A**: Using this result, we characterize the set of distributions of posterior quantiles, which coincide with a monotone function interval. We apply this insight to topics in political economy, Bayesian persuasion, and the psychology of judgment**B**: Furthermore, monotone function intervals provide a common structure to security design. We unify and generalize seminal results in that literature when either adverse selection or moral hazard afflicts the environment.**C**:
We characterize the extreme points of monotone function intervals and apply this result to several economic problems. We show that any extreme point of a monotone function interval must either coincide with one of the monotone function interval’s bounds, or be constant on an interval in its domain, where at least one end of the interval reaches one of the bounds | ACB | ACB | ABC | BCA | Selection 4 |
**A**:
The ‘Remove least-employees firms first’ strategy that aims at minimizing job loss at each individual firm, shown in Fig. 3B manages to keep expected job and output loss at low levels for the initially removed firms**B**: But since this strategy focuses on job loss at the individual firm level, it fails to anticipate a highly systemically relevant firm whose closure results in high levels of expected job and output loss. Since CO2 emissions are not explicitly considered in this strategy, emission savings only rise incrementally with additional firms with comparatively low numbers of employees being removed**C**: To reduce CO2 emissions by 17.35 %, this strategy puts 32.24% of output and 28.41% of jobs at risk, while removing 102 firms from the production network. This strategy therefore fails to secure jobs and economic output, while delivering its emission savings. | CAB | ABC | ACB | BCA | Selection 2 |
**A**: Let us consider the case of a €1B GEB for each GenCo and compare the differences in optimal investment and generation portfolios when increasing TEB from €25M to €50M in a perfectly competitive market. The detailed analysis for this particular example is presented in Figure 5. The arrow in the figure indicates the direction of the power flow**B**: The number with the sign “+” next to it on the left represents the capacity added to the transmission line (in MW). And the number without a sign indicates the total amount of energy transmitted during all time periods through this line (in MWh). The right frame of Figure 5 demonstrates the relative change in the output factors’ values in relation to the values presented on the left**C**: As one can notice, doubling the TEB from €25M to €50M is followed by an increase of 100% in capacity and 99.92% in the flow through the line connecting node 2 (with the highest VRE availability) and node 3 (with the highest demand profile). This transmission capacity expansion motivates GenCos to invest in more VRE generation at node 2, increasing the VRE generation by 19.37% while reducing the conventional generation at node 3 by 11.88%. Ultimately, this new configuration leads to the decrease of GenCos’ costs by 3.20% without any decrease in total generation levels. The latter phenomenon, in turn, leads to an increase in the profit by 4.20% and, hence, the increase in the total welfare as well. This illustrates that, even in this stylised example, the model is capable of capturing the key features of the problem regarding the availability of system connectivity and its effect on Gencos’ motivation to expand their VRE generation.
| ACB | ABC | ACB | CAB | Selection 2 |
**A**:
We analyze the problem of locating a public facility that is considered by some agents in the society a good and by others a bad. Since the Gibbard-Satterthwaite impossibility applies if the set of admissible preferences of each agent includes all single-peaked and all single-dipped preferences, preferences have to be further restricted**B**: We propose a new domain according to which the type of preference of each agent (single-peaked or single-dipped) is known but it is private information as to where each agent’s peak/dip is located and how each agent ranks the rest of the alternatives. This domain fits well with situations in which, even though the location for each agent is publicly known, that location may not necessarily coincide with her peak/dip**C**: For instance, if the public facility is a nursery, parents with children may consider this facility desirable, but it might be undesirable for others without children or for those who prefer to live in a quiet neighborhood. Moreover, despite the fact that home addresses are registered, people spend a considerable amount of time at work and some parents may prefer to have a nursery close to their workplace rather than to their home. Note that such situations cannot be accommodated in the domain of Alcalde-Unzu and | BAC | ABC | BCA | BCA | Selection 2 |
**A**: In addition, these information shocks play a significant role in explaining oil price fluctuations**B**: In general, the results highlight the importance of incorporating information from the stock market into the analysis of oil price movements.**C**:
Overall, the analysis suggests an immediate response of the oil price to stock market information shocks | ACB | BCA | BAC | CBA | Selection 2 |
**A**: Each firm’s production cost is normalized to zero**B**:
There are J𝐽Jitalic_J advertisers (or firms) indexed by j=1,2,…,J𝑗12…𝐽j=1,2,...,Jitalic_j = 1 , 2 , … , italic_J, each selling unique indivisible products and a single digital platform**C**: There is a unit mass of consumers, each | CAB | ACB | BAC | CAB | Selection 3 |
**A**: These have been calculated by multiplying the shares of the flow by the total amount of PR mined. Note that by construction all flows are counted twice, once in the country of origin and once in the country of use.**B**: Color-coded arrows show the flow of P between as well as within countries. The cumulative amounts for each country are shown around the circle**C**:
The flow of P is visualized in more detail in figure 3. The diagram shows the flow of P based on the derived flow matrix for 2021 (FM5superscript𝐹𝑀5F^{M5}italic_F start_POSTSUPERSCRIPT italic_M 5 end_POSTSUPERSCRIPT) | ABC | CBA | CAB | ACB | Selection 2 |
**A**: We show that any stable rule implements, in Nash equilibrium, the individually rational matchings. Second, to implement stable matchings, we focus on another matching game**B**: In some markets, such as school choice or labor markets, institutions are legally required to declare their true preferences (priorities or choice functions), i.e., their preferences are public. In these cases, individuals (students or workers) are expected to manipulate their preference lists to their advantage. This situation leads us to consider a matching game in which the players are only the workers.
**C**: Given a market, the question that arises is what are the rules that induce a matching game that allows us to implement stable matchings in Nash equilibrium. First, we study a matching game in which the players are all the agents | BCA | CBA | ACB | ACB | Selection 1 |
**A**: With this comprehensive homeownership definition, about 70% of individuals in our sample are homeowners (vs 40% if we consider only individuals with a positive open mortgage amount). Second, in an alternative definition of homeownership, we consider the origination of new mortgages**B**: In the analysis, we use the following two definitions of homeownership. First, we consider an individual as a homeowner if either she ever had a mortgage or she is recorded as a homeowner according to Experian’s imputation**C**: In this second case, we define a mortgage origination as a situation in which either the number of open mortgage trades in year t𝑡titalic_t is bigger than the number of open mortgage trades in year t−1𝑡1t-1italic_t - 1 or the number of months since the most recent mortgage trade has been opened is lower than 12. Clearly, this definition would only capture the flow, and perhaps more importantly would miss cash purchases and wouldn’t distinguish between a new mortgage and a remortgage.
| BCA | BAC | ABC | CAB | Selection 2 |
**A**: Note that, given an implementation, neither the distribution which it realizes, nor the underlying decomposition from which a solution is sampled are assumed to be explicitly known (see Section 5.4 for an example)**B**: Clearly, a decomposition of a distribution 𝒅𝒅\bm{d}bold_italic_d implies its implementation, but not vice versa**C**: Given the computational complexity of generating optimal solutions in integer programming, as discussed in Section 3, obtaining a decomposition of a distribution is not always tractable. We will therefore pay special attention to cases in which we can find an implementation of a distribution without first generating its decomposition (see Section 5.4).
| ABC | BCA | ACB | CAB | Selection 1 |
**A**: In particular, it underestimates future low volatility and, most importantly, future high volatility. In fact, while both RV and VIX exhibit scale-free power-law tails, the distribution of the ratio of RV to VIX also has a power-law tail with a relatively small power exponent dashti2019implied ; dashti2021realized , meaning that VIX is incapable of predicting large surges in volatility.
**B**: Since it is based on actual trades, realized volatility (RV) is the ultimate measure of market volatility, although the latter is more often associated with the implied volatility, most commonly measured by the VIX index cboevix ; cboevixhistoric – the so called market ”fear index” – that tries to predict RV of the S&P500 index for the following month. Its model-independent evaluation demeterfi1999guide is based on options contracts, which are meant to predict future stock prices fluctuations whitepaper2003cboe **C**: The question of how well VIX predicts future realized volatility has been of great interest to researchers christensen1998relation ; vodenska2013understanding ; kownatzki2016howgood ; russon2017nonlinear . Recent results dashti2019implied ; dashti2021realized show that VIX is only marginally better than past RV in predicting future RV | ABC | CAB | BAC | CBA | Selection 2 |
**A**: In a different direction,**B**:
Nekipelov et al**C**: (2015) proposes techniques for estimating agents’ valuations in generalized second-price auctions, which stands in contrast to our method that directly utilizes agents’ learning algorithms and is independent of the specific auction format | CBA | ACB | BAC | CAB | Selection 4 |
**A**: first authorship). The first author gains a different amount of credit than the subsequent authors, and one might like to know whether the discrepancy between the credit received by a first author results in first-best research in equilibrium.**B**: However, depending on their contribution to a project, they might receive different levels of credit (e.g**C**:
Researchers are collaborating on a project | CBA | BCA | CAB | BCA | Selection 1 |
**A**: . The subjects were primarily Lancaster University undergraduates (82.2%) from various disciplines, mainly Business and Economics (60%), Social Sciences (23%) and Science and Medicine (17%)101010A potential criticism could be that using a student subject pool could corroborate the results since students tend to be more socially connected compared to a more representative population. Nevertheless, a common finding in the literature is that students tend to behave in a less prosocial way compared to representative populations or professionals (see for example Anderson et al**B**: 2013; Bellemare and Kröger 2007; Belot et al. 2015), giving less in public goods experiments (Gächter et al. 2004; Carpenter and Seki 2011) or behaving in a similar manner to non-student populations (Exadaktylos et al. 2013).**C**:
To test the predictions of the model presented in the previous section, we designed and conducted an incentivised economic experiment. The experiment took place at the Lancaster Experimental Economics Lab (LExEL) in February 2023, involving 96 subjects across three treatments999The power analysis, conducted with a significance level of 0.05 and aiming for 80% power, to detect a moderate effect size (Cohen’s h = 0.65) in the specified one-sided test, indicated a minimum sample of 29.3 subjects per treatment. The power analysis was conducted using the pwr.2p.test function from the library pwr in R | BCA | ACB | ABC | ACB | Selection 1 |
**A**: (2022) study delegation in a more traditional setting using a subject pool of finance professionals and members of the general public, both drawn from the Swedish population**B**: Each investor is matched with an expert who is either a human with fixed or aligned incentives or a robo-advisor, i.e., an appropriately programmed algorithm.222Germann and Merkle (2023), Gaudeul and Giannetti (2023) and Lambrecht et al. (2023) also report experiments where investors can delegate to an algorithm.**C**:
Holzmeister et al | BCA | ABC | ACB | CAB | Selection 1 |
**A**:
We consider bounds on local average treatment effects (LATEs) in instrumental variable models under restrictions on violations of the exclusion restriction**B**: Our previous examples correspond to forms of selection on unobservables**C**: We now show our framework also applies to bounds on local average treatment effects (LATEs) in instrumental variable models under restrictions on violations of the exclusion restriction. | BCA | CBA | BCA | ABC | Selection 4 |
**A**: In subsection 3.2 we introduce a new class of rules called “simple” that play a relevant role in our characterizations and some examples of relevant simple rules are given.**B**:
In this section, we focus on the well-known and widely used domain of single-peaked preferences**C**: In subsection 3.1, three famous rules are asses concerning their obvious manipulability | CAB | BAC | BCA | BCA | Selection 1 |
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