ترغب بنشر مسار تعليمي؟ اضغط هنا

Eliciting Information from Sensitive Survey Questions

49   0   0.0 ( 0 )
 نشر من قبل Yonghong An
 تاريخ النشر 2020
  مجال البحث اقتصاد مالية
والبحث باللغة English




اسأل ChatGPT حول البحث

This paper considers how to elicit information from sensitive survey questions. First we thoroughly evaluate list experiments (LE), a leading method in the experimental literature on sensitive questions. Our empirical results demonstrate that the assumptions required to identify sensitive information in LE are violated for the majority of surveys. Next we propose a novel survey method, called Multiple Response Technique (MRT), for eliciting information from sensitive questions. We require all of the respondents to answer three questions related to the sensitive information. This technique recovers sensitive information at a disaggregated level while still allowing arbitrary misreporting in survey responses. An application of the MRT provides novel empirical evidence on sexual orientation and Lesbian, Gay, Bisexual, and Transgender (LGBT)-related sentiment.

قيم البحث

اقرأ أيضاً

Over the past 200 years, rising rates of information proliferation have created new environments for information competition and, consequently, new selective forces on information evolution. These forces influence the information diet available to co nsumers, who in turn choose what to consume, creating a feedback process similar to that seen in many ecosystems. As a first step towards understanding this relationship, we apply animal foraging models of diet choice to describe the evolution of long and short form media in response to human preferences for maximising utility rate. The model describes an increase in information rate (i.e., entropy) in response to information proliferation, as well as differences in entropy between short-form and long-form media (such as social media and books, respectively). We find evidence for a steady increase in word entropy in diverse media categories since 1900, as well as an accelerated entropy increase in short-form media. Overall the evidence suggests an increasingly competitive battle for our attention that is having a lasting influence on the evolution of language and communication systems.
325 - Zhengyu Shi , Libo Wu , Haoqi Qian 2021
Inferring the uncertainties in economic conditions are of significant importance for both decision makers as well as market players. In this paper, we propose a novel method based on Hidden Markov Model (HMM) to construct the Economic Condition Uncer tainty (ECU) index that can be used to infer the economic condition uncertainties. The ECU index is a dimensionless index ranges between zero and one, this makes it to be comparable among sectors, regions and periods. We use the daily electricity consumption data of nearly 20 thousand firms in Shanghai from 2018 to 2020 to construct the ECU indexes. Results show that all ECU indexes, no matter at sectoral level or regional level, successfully captured the negative impacts of COVID-19 on Shanghais economic conditions. Besides, the ECU indexes also presented the heterogeneities in different districts as well as in different sectors. This reflects the facts that changes in uncertainties of economic conditions are mainly related to regional economic structures and targeted regulation policies faced by sectors. The ECU index can also be easily extended to measure uncertainties of economic conditions in different fields which has great potentials in the future.
Economists have predicted that damages from global warming will be as low as 2.1% of global economic production for a 3$^circ$C rise in global average surface temperature, and 7.9% for a 6$^circ$C rise. Such relatively trivial estimates of economic d amages -- when these economists otherwise assume that human economic productivity will be an order of magnitude higher than today -- contrast strongly with predictions made by scientists of significantly reduced human habitability from climate change. Nonetheless, the coupled economic and climate models used to make such predictions have been influential in the international climate change debate and policy prescriptions. Here we review the empirical work done by economists and show that it severely underestimates damages from climate change by committing several methodological errors, including neglecting tipping points, and assuming that economic sectors not exposed to the weather are insulated from climate change. Most fundamentally, the influential Integrated Assessment Model DICE is shown to be incapable of generating an economic collapse, regardless of the level of damages. Given these flaws, economists empirical estimates of economic damages from global warming should be rejected as unscientific, and models that have been calibrated to them, such as DICE, should not be used to evaluate economic risks from climate change, or in the development of policy to attenuate damages.
In this paper, we first revisit the Koenker and Bassett variational approach to (univariate) quantile regression, emphasizing its link with latent factor representations and correlation maximization problems. We then review the multivariate extension due to Carlier et al. (2016, 2017) which relates vector quantile regression to an optimal transport problem with mean independence constraints. We introduce an entropic regularization of this problem, implement a gradient descent numerical method and illustrate its feasibility on univariate and bivariate examples.
How does food consumption improve educational outcomes is an important policy issue for developing countries. Applying the Indonesian Family Life Survey (IFLS) 2014, we estimate the returns of food consumption to education and investigate if more edu cated individuals tend to consume healthier bundles than less-educated individuals do. We implement the Expected Outcome Methodology, which is similar to Average Treatment on The Treated (ATT) conceptualized by Angrist and Pischke (2009). We find that education tends to tilt consumption towards healthier foods. Specifically, individuals with upper secondary or higher levels of education, on average, consume 31.5% more healthy foods than those with lower secondary education or lower levels of education. With respect to unhealthy food consumption, more highly-educated individuals, on average, consume 22.8% less unhealthy food than less-educated individuals. This suggests that education can increase the inequality in the consumption of healthy food bundles. Our study suggests that it is important to design policies to expand education for all for at least up to higher secondary level in the context of Indonesia. Our finding also speaks to the link between food-health gradient and human capital formation for a developing country such as Indonesia.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا