Banyere
Ọrụ m na-anọdụ na njikọta nke mmepe akụ na ụba, ọrụ ugbo, okike, na nha na mba ndị na-emepe emepe. M na-eji nnukwu nyocha ezinụlọ na data geospatial iji mụọ etu ezinụlọ, ugbo, na ahịa si arụ ọrụ, ọkachasị na ntọala ebe data dị ụkọ ma ọ bụ sie ike ịnakọta. Enwetara m PhD m na Graduate Institute na Geneva ma rụọ ọrụ na data nyocha na IFPRI, IMF, na World Bank.
M tọrọ ntọala Dollar Scholars, ntọala nke na-enye agụmakwụkwọ ego dabere na ihe akaebe nye ndị okenye nwere ike ọ gaghị enwe ike ịnweta ya. M wuru ebe nrụọrụ weebụ ya na ajụjụ ọtụtụ asụsụ.
Tupu akụ na ụba, m nọrọ afọ asaa dị ka ọkachamara eSports commentator, na-akpọ Counter-Strike na Warcraft III tournaments si Seoul ka Monza n'etiti 2004 na 2011. M ka na-egwu Counter-Strike 2 na Overwatch 2, ma na-awakpo dị ka bard na EverQuest.
Nnyocha
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Akwụkwọ ọrụ
Spreading the love around: how does agricultural labor demand respond to temporary weather shocks?
N'ime mba isii, ezinụlọ ndị ọrụ ugbo na-adabere n'ọrụ ezinụlọ n'oge oké ọkọchị na oge mmiri ozuzo na-adịghị ahụkebe. Ezinụlọ ndị na-eduzi ụmụ nwanyị na-enwe nsogbu karịa.
Nchịkọta
This is the first study to separately identify labor demand responses to both unanticipated droughts and periods of above normal rainfall for three forms of agricultural labor that are central to agricultural production: family, hired, and mutual exchange labor. I use a simple parcel‑level model with three labor types and monitoring costs to study how family labor is reallocated across parcels during drought. In six countries I find small but statistically significant decreases in the share of hired labor during droughts and during periods of above-normal rainfall, indicating a strong reliance on family labor during shocks. I find that farm households appear to lean heavily on exchange labor by using exchange labor more frequently during periods of above-normal rainfall. Due to the heavy reliance on family labor, household size and the gender of the household head are important moderating factors. Women-headed households appear to be significantly more constrained in how they apply labor on family farms. My findings underscore that these labor types are distinct in how they respond to temporary weather shocks. The results of my analysis have important implications for policies targeted at stimulating agricultural labor markets.
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Ọrụ na-aga n'ihu
Assessing land area from above: evidence from Armenia
Nnwale a na-enweghị usoro n'ime nyocha ezinụlọ: nchọpụta ubi na onyonyo satịlaịtị were 42% obere oge karịa ịtụle na GPS ma melite na atụmatụ onwe onye, ọ bụ ezie na ọ bụ obere ihe ziri ezi karịa GPS.
Nchịkọta
Using primary data collected by the World Bank in Armenia as part of a randomized controlled trial, we evaluate the use of a satellite image tracing to measure agricultural land in the context of a household survey. Satellite tracing offers several benefits, including a large reduction in the cost of measuring land, the potential to measure more parcels of land, and improved security for survey enumerators. We find the satellite tracing approach yields consistent results, and requires 42% less time than measuring with GPS, and provides value-added over self-reported estimates. Due to the potential cost savings, and other non-trivial benefits, we suggest that land measurement via satellite image tracing offers significant value, though is not as accurate as land area estimates conducted with a handheld GPS.
Ozizi
Ọ bụ n'ezie otu n'ime prọfesọ kachasị mma m nwetụrụla na Mahadum America. Ọ na-apụ n'ụzọ ya ka klas ahụ jiri ezigbo ihe atụ nke data kama inwe 'Sally nwere apụl 4 na Dave nwere nsogbu ụdị oroma 15... Ọ bụ ihe niile prọfesọ kọleji kwesịrị ịbụ, na ụfọdụ.
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2021 – 2024
Adjunct Prọfesọ · Mahadum America
Mmepe akụ na ụba, etinyere econometrics, na mmeghe micro- na macroeconomics, kụziiri na ezigbo data na ezigbo ihe atụ ụwa.
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2015 – 2018
Graduate Institute, Geneva
Economics for International Affairs (2015–2016) na nnọkọ nyocha maka Macroeconomics A (2017–2018).
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Obodo
Economics Discord
A 501 (c) (3) agụmakwụkwọ na-abaghị uru na onye mmekọ Discord ebe ihe karịrị ụmụ akwụkwọ akụ na ụba 3,000, ndị na-eme nchọpụta na ndị na-ahụ maka akụ na ụba sitere na mba 30 na-enyere ibe ha aka ịmụta.
Dollar Scholars
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Onye guzobere
Dollar Scholars
Ntọala maka agụmakwụkwọ ego ndị okenye, nke a kụziiri n'onwe ya ma dabere na nyocha, n'ihi na kredit enweghị ike inyere ndị na-amaghị etu esi eji ya aka.
Mmemme
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Mmepe weebụ
dollarscholars.org
M chepụtara, koodu ma sụgharịa ebe nrụọrụ weebụ ntọala ahụ: saịtị Django omenala nke ejiri Tailwind CSS ma kwadoro onwe ya na nginx na ihe nkesa Ubuntu, wughachiri na nchekwa n'uche mgbe mwakpo cyber. Ọ na-abịa na nsụgharị asụsụ 44, gụnyere asụsụ anọ gaa n'aka ekpe (Arabic, Hibru, Peasia na Urdu), na ndị ntụgharị afọ ofufo nwere ike ịlele ma mezie ụdị ọ bụla site na arụmọrụ CSV dị mfe.
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Financial Knowledge Study
A multilingual ego-ihe ọmụma nnyocha na ajụjụ na 31 asụsụ, gbakwunyere ise playful ndị dị ka Pirate Speak na 1930s Mobster. A na-agbanwe ajụjụ site na Lusardi & Mitchell (2014) na FINRA Foundation's National Financial Capability Study; edere nsụgharị na Microsoft Copilot na Deep Translator ma nyochaa ya site n'aka ndị ọrụ afọ ofufo ebe ọ dị.
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Nnyocha nyocha
Data na nyocha geospatial
Python (pandas) na Stata maka nnukwu datasets dị ka nyocha ezinụlọ, na GIS (ArcGIS) maka data satịlaịtị, gụnyere eserese VIIRS ọkụ abalị n'azụ weebụsaịtị a.
Nkọwa nke eSports
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2004 – 2011
eSports Commentator
A na-akpọ Counter-Strike 1.6 na Warcraft III maka ndị mgbasa ozi gụnyere DirecTV, MTV na MTV Korea, n'akụkụ ndị na-eme ihe nkiri dị ka Alex “Vansilli” Nguyen, Glenn “Boomerman” Lane na Zach “Hoo_man” Godfrey.
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Pịa · MTV.com (archived)
Video game play-by-play comes with a deadly challenge