wanyu/IteraTeR_full_sent huggingface dataset:
Original:  We characterize sharp bounds on the joint distribution of potential outcomes and the identifying power of exclusion restrictions. The latter include variables that affect market conditions only in one sector and variables that affect sector selection only . Special emphasis is put on the case of binary outcomes, which has received little attention in the literature to date.
Revised:  We characterize sharp bounds on the joint distribution of potential outcomes and testable implications of the Roy self-selection model under an instrumental constraint on the joint distribution of potential outcomes we call stochastically monotone instrumental variable (SMIV). We show that testing the Roy model selection is equivalent to testing stochastic monotonicity of observed outcomes relative to the instrument. We apply our sharp bounds to the derivation of a measure of departure from Roy self-selection to identify values of observable characteristics that induce the most costly misallocation of talent and sector and are therefore prime targets for intervention . Special emphasis is put on the case of binary outcomes, which has received little attention in the literature to date.
Edit intent: meaning-changed
Original:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data traffic charges for accessing content from certain CPs or applications (zero-rated) and apply regular charges for accessing content from other CPs.
Revised:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data access charges for on content from certain CPs or applications (zero-rated) and apply regular charges for accessing content from other CPs.
Edit intent: clarity
Original:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data traffic charges for accessing content from certain CPs or applications (zero-rated) and apply regular charges for accessing content from other CPs.
Revised:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data traffic charges for accessing content from certain CPs (zero-rated) and apply regular charges for accessing content from other CPs.
Edit intent: clarity
Original:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data traffic charges for accessing content from certain CPs or applications (zero-rated) and apply regular charges for accessing content from other CPs.
Revised:  In the differential pricing scheme, Internet Service Providers (ISPs) can exempt data traffic charges for accessing content from certain CPs or applications (zero-rated) while no exemption is on content from other CPs.
Edit intent: clarity
Original:  We show that in a differential pricing regime 1) a CP offering low QoS can make more revenues than a CP offering better QoS through sponsorships. 2)  QoS (mean delay) for end users can degrade compared to the case where no differential pricing is allowed .
Revised:  We show that in a differential pricing regime 1) a CP offering low QoS can make have higher surplus than a CP offering better QoS through sponsorships. 2) QoS (mean delay) for end users can degrade compared to the case where no differential pricing is allowed .
Edit intent: meaning-changed
Original:  We show that in a differential pricing regime 1) a CP offering low QoS can make more revenues than a CP offering better QoS through sponsorships. 2)  QoS (mean delay) for end users can degrade compared to the case where no differential pricing is allowed .
Revised:  We show that in a differential pricing regime 1) a CP offering low QoS can make more revenues than a CP offering better QoS through sponsorships. 2) Overall QoS (mean delay) for end users can degrade compared to the case where no differential pricing is allowed .
Edit intent: meaning-changed
Original:  We show that in a differential pricing regime 1) a CP offering low QoS can make more revenues than a CP offering better QoS through sponsorships. 2)  QoS (mean delay) for end users can degrade compared to the case where no differential pricing is allowed .
Revised:  We show that in a differential pricing regime 1) a CP offering low QoS can make more revenues than a CP offering better QoS through sponsorships. 2) QoS (mean delay) for end users can degrade under differential pricing schemes. In the oligopolistic market with multiple ISPs, users tend to select the ISP with lowest ISP resulting in same type of conclusions as in the monopolistic market. We then study how differential pricing effects the revenue of ISPs .
Edit intent: meaning-changed
Original:  Our second result says that the scaling limit of super--replication prices for binomial models with a fixed number moments of delay is equal to the G--expectation with volatility uncertainty interval which we compute explicitly .
Revised:  Our second result says that the scaling limit of super--replication prices for binomial models with a fixed number of times of delay H is equal to the G--expectation with volatility uncertainty interval which we compute explicitly .
Edit intent: meaning-changed
Original:  Our second result says that the scaling limit of super--replication prices for binomial models with a fixed number moments of delay is equal to the G--expectation with volatility uncertainty interval which we compute explicitly .
Revised:  Our second result says that the scaling limit of super--replication prices for binomial models with a fixed number moments of delay is equal to the G--expectation with volatility uncertainty interval 0,\sigma\sqrt{H+1 .
Edit intent: meaning-changed
Original:  With products differentiated along a quality index and agents characterized by scalar unobserved heterogeneity, single crossing conditions on preferences and technology provide identifying restrictions  .
Revised:  With products differentiated along a quality index and agents characterized by scalar unobserved heterogeneity, single crossing conditions on preferences and technology provide identifying restrictions in Ekeland, Heckman and Nesheim (2004) and Heckman, Matzkin and Nesheim (2010) .
Edit intent: meaning-changed
Original:  We thereby extend identification results in Matzkin (2003) and Heckman, Matzkin and Nesheim (2004) to accommodate multiple dimensions of unobserved heterogeneity.
Revised:  We thereby derive nonparametric identification results for nonseparable simultaneous equations and multi-attribute hedonic equilibrium models with (possibly) multiple dimensions of unobserved heterogeneity.
Edit intent: meaning-changed
Original: In many macroeconomic applications, impulse responses and their (bootstrap) confidence intervals are constructed by estimating a VAR model in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank.
Revised: In many macroeconomic applications, impulse responses and their frequentist confidence intervals are constructed by estimating a VAR model in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank.
Edit intent: meaning-changed
Original:  While it is well known that using a wrong cointegration rank leads to invalid (bootstrap) inference, we demonstrate that even if the rank is consistently estimated, ignoring uncertainty regarding the true rank can make inference highly unreliable for sample sizes encountered in macroeconomic applications. We investigate the effects of rank uncertainty in a simulation study, comparing several methods designed for handling model uncertainty .
Revised:  In this paper we investigate the consequences of ignoring this uncertainty. We adapt several proposed methods for handling model uncertainty .
Edit intent: clarity
Original:  We investigate the effects of rank uncertainty in a simulation study, comparing several methods designed for handling model uncertainty . We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way and outperforms all other methods considered in the simulation study.
Revised:  We investigate the effects of rank uncertainty in a simulation study, comparing several methods designed for handling model uncertainty to perform inference in cointegrated VAR models and highlight their shortcomings in the present setting. Therefore, we propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way and outperforms all other methods considered in the simulation study.
Edit intent: meaning-changed
Original:  We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way and outperforms all other methods considered in the simulation study.
Revised:  We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way . In a simulation study the WIMP method outperforms all other methods considered in the simulation study.
Edit intent: clarity
Original:  We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way and outperforms all other methods considered in the simulation study. The WIMP method is shown to deliver intervals that are robust to rank uncertainty, yet allow for meaningful inference, approaching fixed rank intervals when evidence for a particular rank is strong.
Revised:  We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way and outperforms all other methods considered , delivering intervals that are robust to rank uncertainty, yet allow for meaningful inference, approaching fixed rank intervals when evidence for a particular rank is strong.
Edit intent: clarity
Original:  The WIMP method is shown to deliver intervals that are robust to rank uncertainty, yet allow for meaningful inference, approaching fixed rank intervals when evidence for a particular rank is strong. We study the potential ramifications of rank uncertainty on applied macroeconomic analysis by re-assessing the effects of fiscal policy shocks based on a variety of identification schemes that have been considered in the literature .
Revised:  The WIMP method is shown to deliver intervals that are robust to rank uncertainty, yet not overly conservative. We also study the potential ramifications of rank uncertainty on applied macroeconomic analysis by re-assessing the effects of fiscal policy shocks based on a variety of identification schemes that have been considered in the literature .
Edit intent: clarity
Original: In many macroeconomic applications, impulse responses and their frequentist confidence intervals are constructed by estimating a VAR model in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank .
Revised: In many macroeconomic applications, impulse responses and their frequentist confidence intervals are constructed by estimating VAR models in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank .
Edit intent: fluency
Original: In many macroeconomic applications, impulse responses and their frequentist confidence intervals are constructed by estimating a VAR model in levels - thus ignoring uncertainty regarding the true (unknown) cointegration rank . In this paper we investigate the consequences of ignoring this uncertainty.
Revised: In many macroeconomic applications, impulse responses and their frequentist confidence intervals are constructed by estimating a VAR model in levels - ignoring cointegration rank uncertainty. We investigate the consequences of ignoring this uncertainty.
Edit intent: clarity
Original:  We adapt several proposed methods for handling model uncertainty to perform inference in cointegrated VAR models and highlight their shortcomings in the present setting. Therefore, we propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way.
Revised:  We adapt several proposed methods for handling model uncertainty to perform inference in cointegrated VAR models and highlight their shortcomings . We propose a new method - Weighted Inference by Model Plausibility (WIMP) - that takes rank uncertainty into account in a fully data-driven way.
Edit intent: coherence
Original:  We also study the potential ramifications of rank uncertainty on applied macroeconomic analysis by re-assessing the effects of fiscal policy shocks based on a variety of identification schemes. We demonstrate how sensitive the results are to the treatment of the cointegration rank, and show how formally accounting for rank uncertainty can affect the conclusions .
Revised:  We also study the potential ramifications of rank uncertainty on applied macroeconomic analysis by re-assessing the effects of fiscal policy shocks .
Edit intent: clarity
Original: The purpose of this paper is to present a new approach to construct optimal portfolios and investment strategies based on stock return predictions. Recurrent Neural Networks (RNNs)  are applied to stock return predictions.
Revised: This paper aims at developing a new method by which to build a data-driven portfolio featuring a target risk-return. We first present a comparative study of recurrent neural network models (RNNs) are applied to stock return predictions.
Edit intent: meaning-changed
Original:  We build portfolios by adjusting potential return threshold levels used to classify assets, and obtain  risk-return profiles examining their statistical properties.
Revised:  We build portfolios by adjusting potential return threshold levels used to classify assets, and obtain P500. The experimental results shows that LSTM outperforms the others in terms of hit ratio of one-month-ahead forecasts. We then build predictive threshold-based portfolios (TBPs) that are subsets of the universe satisfying given threshold criteria for the predicted returns. The TBPs are rebalanced monthly to restore equal weights to each security within the TBPs. We find that the risk and return profile of the realized TBP represents a monotonically increasing frontier on the risk-return profiles examining their statistical properties.
Edit intent: meaning-changed
Original:  We build portfolios by adjusting potential return threshold levels used to classify assets, and obtain  risk-return profiles examining their statistical properties. The results show conclusively that the thresholds control the level of risk-return trade-off, which can be usefully implemented in allocating assets across asset classes based on individual risk capacity and risk tolerance levels.
Revised:  We build portfolios by adjusting potential return threshold levels used to classify assets, and obtain risk-return plane, where the equally weighted portfolio (EWP) of all ten stocks plays a role in their lower bound. This shows the availability of TBPs in targeting specific risk-return trade-off, which can be usefully implemented in allocating assets across asset classes based on individual risk capacity and risk tolerance levels.
Edit intent: meaning-changed
Original:  The results show conclusively that the thresholds control the level of risk-return trade-off, which can be usefully implemented in allocating assets across asset classes based on individual risk capacity and risk tolerance levels. Next, we obtain frontier lines representing the risk-reward relationship for portfolios built using three strategies (e. g., long, short, and long-short), and then determine the efficient frontier that maximizes returns at specific risk levels. We thus find optimal investment strategies using portfolios tailored to an investor's riskpreference .
Revised:  The results show conclusively that the thresholds control the level of risk-return levels, and an EWP based on all the assets plays a role in the reference portfolio of TBPs. In the process, thresholds play dominant roles in characterizing risk, return, and the prediction accuracy of the subset. The TBP is more data-driven in designing portfolio target risk and return than existing ones, in the sense that it requires no prior knowledge of finance such as financial assumptions, financial mathematics, or expert insights. In a practical application, we present the TBP management procedure for a time horizon extending over multiple time periods; we also discuss their application to mean-variance portfolios to reduce estimation risk .
Edit intent: meaning-changed
Original:  We find that quick learners develop both higher dimensional and more compact responses to stimuli than slow learners, suggesting a greater efficiency in embedding rich patterns of information. Using a virtual lesioning approach ,  we identify which regions form the strongest neurophysiological drivers of these differences in learning rate .
Revised:  We find that quick learners develop both higher dimensional and more compact responses to stimuli , we identify which regions form the strongest neurophysiological drivers of these differences in learning rate .
Edit intent: clarity
Original:  Using a virtual lesioning approach ,  we identify which regions form the strongest neurophysiological drivers of these differences in learning rate . We complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses , providing evidence that higher dimensional responses also characterize patterns of activation within regions known to process and represent objects and their values .
Revised:  Using a virtual lesioning approach , we identify which regions form the strongest neurophysiological drivers of these differences in learning rate , and complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses , providing evidence that higher dimensional responses also characterize patterns of activation within regions known to process and represent objects and their values .
Edit intent: coherence
Original: Theories and tools to measure the efficiency of neural codes have been important in understanding neural responses to external stimuli. However, similar principles to describe the efficiency of brain responses to tasks demanding higher-order cognitive processes remain underdeveloped. A key domain to study such efficiency is learning, where patterns of activity across the entire brain provide insight into the principles governing the acquisition of knowledge about objects or concepts. We propose a mathematical framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects .
Revised: A fundamental cognitive process is the ability to map objects into meaningful categories depending on the task at hand. Exactly how such mental constructs emerge and what kind of space best embeds this mapping remains incompletely understood. Here we develop tools to quantify the space URLanization of such a mapping, thereby providing a framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects .
Edit intent: clarity
Original:  We propose a mathematical framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects . We find that compared to slow learners, quick learners use a smaller ambient embedding to simultaneously encode higher dimensional patterns of neural responses to stimuli, providing a notion of effective codingmost associated with rapid learning.
Revised:  We propose a mathematical framework for studying the efficiency of spatially embedded whole-brain states reflected in functional MRI , and demonstrate its utility in describing how human subjects learn the values of novel objects , we show that quick learners have a higher dimensional geometric representation than slow learners, quick learners use a smaller ambient embedding to simultaneously encode higher dimensional patterns of neural responses to stimuli, providing a notion of effective codingmost associated with rapid learning.
Edit intent: meaning-changed
Original:  We find that compared to slow learners, quick learners use a smaller ambient embedding to simultaneously encode higher dimensional patterns of neural responses to stimuli, providing a notion of effective codingmost associated with rapid learning. Furthermore, we identify which regions form the strongest neurophysiological drivers of these differences in learning rate, and complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses.
Revised:  We find that compared to slow learners, and hence more easily distinguishable whole-brain responses to objects of different value. Furthermore, we find that quick learners display a more compact embedding of the task-relevant information, where the ratio of task-relevant dimension to embedding dimension is consistent with a greater efficiency of cognitive coding. Lastly, we investigate the neurophysiological drivers of these differences in learning rate, and complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses.
Edit intent: meaning-changed
Original:  Furthermore, we identify which regions form the strongest neurophysiological drivers of these differences in learning rate, and complement our region-based approach with a voxel-level approach to uncover structure in finer-scale responses. Finally, for a full investigation of complementary geometric approaches, we verify that quick learners develop more assortative responses to stimuli: that is, whole-brain responses that are more easily distinguishable from one another.
Revised:  Furthermore, we identify which regions form the strongest neurophysiological drivers of high dimensional patterns at both regional and voxel levels, and complete our study with a complementary test of the distinguishability of associated whole-brain responses that are more easily distinguishable from one another.
Edit intent: clarity
Original:  Finally, for a full investigation of complementary geometric approaches, we verify that quick learners develop more assortative responses to stimuli: that is, whole-brain responses that are more easily distinguishable from one another. Our work offers a suite of geometric measures to represent a notion of efficient coding for higher-order cognitive processes, and provide insight into the dimensionality of neural responses characteristic of the successful optimization of reward, that are applicable to the study of cognitive performance more broadly.
Revised:  Finally, for a full investigation of complementary geometric approaches, we verify that quick learners develop more assortative responses to stimuli: that is, whole-brain responses . Our results demonstrate a URLanization of neural responses characteristic of the successful optimization of reward, that are applicable to the study of cognitive performance more broadly.
Edit intent: clarity
Original:  Our work offers a suite of geometric measures to represent a notion of efficient coding for higher-order cognitive processes, and provide insight into the dimensionality of neural responses characteristic of the successful optimization of reward, that are applicable to the study of cognitive performance more broadly.
Revised:  Our work offers a suite of geometric measures to represent a notion of efficient coding for higher-order cognitive processes, and provide insight into the dimensionality of neural responses characteristic of learning, and offer a suite of geometric measures applicable to the study of cognitive performance more broadly.
Edit intent: clarity