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Moslem Rashidi

Publications and source records attributed to Moslem Rashidi.

8 recordsLinked to original sources
arXiv2026

Effects of interviewers on response to income and wealth items

Item nonresponse to financial questions is a persistent source of survey error, especially in interviewer-administered surveys. We examine whether interviewers' expectations about respondents' willingness to report income are associated with actual item responses to income and asset questions in Wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE). Using data from 41,934 respondents in 12 countries, linked to interviewer survey and roster information, we analyze responses to four financial items with substantial nonresponse. We compare three approaches to handling missing covariates: complete-case analysis, multiple imputation (fill-in methods), and a generalized missing-indicator framework with information-criterion-based model averaging. Across most specifications, respondents interviewed by interviewers with higher expected income response rates are more likely to provide financial information. However, model averaging does not yield clear gains over simpler approaches. The results suggest that interviewer expectations contain useful information for understanding and modeling item nonresponse to sensitive financial items, with potential implications for interviewer training and survey fieldwork design.

econ.GN↗
arXiv2026

Heart Failure's First Shock and Nurse-Led Chronic Care

We study how a first heart-failure hospitalization, an adverse health shock, changes patients' care, and whether a nurse-led chronic-care program sustains those post-shock investments. Using linked population-wide administrative records from Italy's Romagna Local Health Authority (2017-2023), we anchor event time at each patient's first CHF admission and exploit staggered timing to estimate dynamic effects. The shock triggers a sharp post-discharge surge: beta-blocker adherence, cardiology follow-up, and echocardiography rise immediately, while emergency-room use spikes just before admission and then stabilizes. We then estimate the incremental impact of enrollment in the Nurse-led Program for Chronic Patients (NPCP) using the interaction-weighted event-study estimator for staggered adoption. Under conventional difference-in-differences inference, NPCP strengthens long-run preventive engagement, with little detectable change in emergency-room use. HonestDiD sensitivity analysis indicates these gains are economically meaningful but not statistically definitive under modest departures from parallel trends.

econ.GN↗
arXiv2025

The Emergency-Care Consequences of Disrupted Prevention: Evidence from Mammography Screening Pathway

Do disruptions to organized preventive-care pathways increase the likelihood of downstream overnight emergency hospitalizations? We study this question using the COVID-19 pandemic as a natural experiment. Using SHARE Wave~9 data on women aged 50--69 in eight European countries, we instrument for mammography uptake -- an observable indicator of access to organized preventive-care pathways -- with the interaction between country-level pandemic restriction intensity and SHARE interview-month cohort. This variation is plausibly exogenous because fieldwork timing shifted the portion of the 2020 restriction period that fell within each respondent's two-year recall window, generating differential disruption to screening access across cohorts within countries. The OLS estimates are close to zero, consistent with selection based on health status. However, the IV results imply that mammography uptake reduces the probability of overnight emergency hospitalization by approximately 6 percentage points among compliers. LIML produces a statistically significant estimate of $-0.114$. Women aged 70 and above, who are outside organized screening programs in all eight countries, show no first-stage and no reduced-form evidence of an effect on overnight emergency hospitalization. A decomposition exercise confirms that the breast-cancer detection channel accounts for at most 6 percent of the estimate, pointing instead to broader preventive-pathway disruption.

econ.GN↗
arXiv2012

A full-custom ASIC design of a 8-bit, 25 MHz, Pipeline ADC using 0.35 um CMOS technology

The purpose of this project was to design and implement a pipeline Analog-to-Digital Converter using 0.35um CMOS technology. Initial requirements of a 25-MHz conversion rate and 8-bits of resolution where the only given ones. Although additional secondary goals such as low power consumption and small area were stated. The architecture is based on a 1.5 bit per stage structure utilizing digital correction for each stage [12]. A differential switched capacitor circuit consisting of a cascade gm-C op-amp with 200MHz ft is used for sampling and amplification in each stage [12]. Differential dynamic comparators are used to implement the decision levels required for the 1.5-b per stage structure. Correction of the pipeline is accomplished by using digital correction circuit consist of D-latches and full-adders. Area and Power consumption of whole design was 0.24mm2 and 35mW respectively. The maximum sample rate at which the converter gave an adequate output was 33MHz.

cs.AR↗
arXiv2010

Parameter Selection in Periodic Nonuniform Sampling of Multiband Signals

Periodic nonuniform sampling has been considered in literature as an effective approach to reduce the sampling rate far below the Nyquist rate for sparse spectrum multiband signals. In the presence of non-ideality the sampling parameters play an important role on the quality of reconstructed signal. Also the average sampling ratio is directly dependent on the sampling parameters that they should be chosen for a minimum rate and complexity. In this paper we consider the effect of sampling parameters on the reconstruction error and the sampling ratio and suggest feasible approaches for achieving an optimal sampling and reconstruction.

eess.SY↗
arXiv2010

A Wideband Spectrum Sensing Method for Cognitive Radio using Sub-Nyquist Sampling

Spectrum sensing is a fundamental component in cognitive radio. A major challenge in this area is the requirement of a high sampling rate in the sensing of a wideband signal. In this paper a wideband spectrum sensing model is presented that utilizes a sub-Nyquist sampling scheme to bring substantial savings in terms of the sampling rate. The correlation matrix of a finite number of noisy samples is computed and used by a subspace estimator to detect the occupied and vacant channels of the spectrum. In contrast with common methods, the proposedmethod does not need the knowledge of signal properties that mitigates the uncertainty problem. We evaluate the performance of this method by computing the probability of detecting signal occupancy in terms of the number of samples and the SNR of randomly generated signals. The results show a reliable detection even in low SNR and small number of samples.

cs.IT↗
arXiv2010

Non-uniform sampling and reconstruction of multi-band signals and its application in wideband spectrum sensing of cognitive radio

Sampling theories lie at the heart of signal processing devices and communication systems. To accommodate high operating rates while retaining low computational cost, efficient analog-to digital (ADC) converters must be developed. Many of limitations encountered in current converters are due to a traditional assumption that the sampling state needs to acquire the data at the Nyquist rate, corresponding to twice the signal bandwidth. In this thesis a method of sampling far below the Nyquist rate for sparse spectrum multiband signals is investigated. The method is called periodic non-uniform sampling, and it is useful in a variety of applications such as data converters, sensor array imaging and image compression. Firstly, a model for the sampling system in the frequency domain is prepared. It relates the Fourier transform of observed compressed samples with the unknown spectrum of the signal. Next, the reconstruction process based on the topic of compressed sensing is provided. We show that the sampling parameters play an important role on the average sample ratio and the quality of the reconstructed signal. The concept of condition number and its effect on the reconstructed signal in the presence of noise is introduced, and a feasible approach for choosing a sample pattern with a low condition number is given. We distinguish between the cases of known spectrum and unknown spectrum signals respectively. One of the model parameters is determined by the signal band locations that in case of unknown spectrum signals should be estimated from sampled data. Therefore, we applied both subspace methods and non-linear least square methods for estimation of this parameter. We also used the information theoretic criteria (Akaike and MDL) and the exponential fitting test techniques for model order selection in this case.

cs.IT↗