Job Nmadu, Professor of Agricultural Economics specializing in Econometrics

Academic, Teacher, Researcher, Consultant, Administrator and Community Leader with skills in Data Science and Machine Learning Modelling with R; Computable General Equilibrium Modellng with GAMS and Students Advisor (Undergraduates, Masters and Doctoral).

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Skills

Data Collection, Wrangling, Analysis and Visualisation

85%

Leadership, Administration and Coordination

80%

Modelling, Data Science, Machine Learning, R/CGE Programming

70%

Research, Consultancy, Collaboration and Networking

75%

Recent Publications

Forecasting leads to adequate and comprehensive planning for sustainable development. A number of procedures are used to estimate, predict and forecast data, but not all are able to capture the historical path of the data generating process adequately. In view of this, the timeseries characteristics, structural changes and trend of inflation in Nigeria (1996-2022) were analyzed using ARMA, Holt-Winters, spline and other associated models. The results indicated that inflation in Nigeria has remained above acceptable limits in a cyclical trend during the period under study and that there is every possibility that Nigerian inflation would remain above 10% for some time to come. There were six shocks, the major stressors being food inflation, oil and gas prices and wages adjustment. For Nigeria to achieve a stable inflation rate regime of acceptable limits, a robust economic management and intelligence team using a global innovation platform as well as evidencedbased policies which ensure that Nigeria does not swerve away from the path to recovery should be established in consultation with the fiscal, monetary, and research authorities.

The study analyzed factors that influence farmers' access to extension services in the study area. The study utilized data obtained from 483 farmers with the use of interview schedule questionnaire. The data were analyzed using vtree and Double hurdle regression model. The results revealed that 80% of the respondents are male with moderate adaptive capacity to climate change. In addition, farmers, with high adaptive capacity to climate change had higher level of education. Result of the double hurdle regression revealed that farmer’s adaptive capacity to climate change, being a male, farm income, non-farm income, being poor, availability of social amenities, membership of association and increase in the distance of farmer‘s farm from the village had significant positive influence of number of extension services received by farmers with contacts. While ratio of livelihood activities, farm size, age, level of education, distance of farm to market, credit, livestock ownership, household size and working household members had significant negative influence on number of extension services received by farmers with contact. Furthermore, result of the zero-contact revealed that the odds can be increased by adaptive capacity to climate change, farm size, gender, credit, household size, poverty status, availability of social amenities and membership of association. While ratio of livelihood activities, livestock ownership and farming experience can decrease extension contact. It was there for recommended that extension agents should assist in increasing the adaptive capacity of the farmers by incorporating more climate change related techniques and adaptation strategies in their services, availability of functional social amenities should be a major focus when formulating policies and developmental issues as it influences extension services and farmers should be encourage to form associations so as to achieve the benefits associated with it.

The study examined the ability to minimize cost and maximize income among women marketers participating in donor-assisted programmes in Lavun Local Government Area, Niger State. The specific objectives are to describe their demographic and institutional characteristics of the women marketers, examine the level and effectiveness of participation of the women in the programmes, determine the factors that promote cost minimization or income maximization and identify the constraints that hindered the women participation the programmes. A multistage sampling technique was used to select 100 women from three (3) districts (Gaba, Doko and Jima) in the study area. The data were generated through the use of questionnaire. Data collected were analyzed using descriptive and Ordinary Least Square regression model. The result of the findings revealed mean age of the women, farming experience, household size and year of school were 38, 12, 8 and 10 respectively. The mean income realized from marketing agricultural produce was NGN90,580.00, while mean cost incurred was NGN77,880.00. However, age, marital status, sale of provision, constraint not very serious and television as sources of information were the factors that promote minimize cost and maximize income among market women that participated in donor-assisted programmes. Constraints that hindered the market women participation in donor-assisted programme were marketing cost, illiteracy, inaccessibility, gender discrimination, non-availability, complexity, lack of awareness, lack of confidence and corruption. It was therefore recommended that market women should be encouraged to participate effectively in the programmes so as to increase their level of participation and also take the advantages associated with it. The market women should diversify their sources on income in to sales of provision in addition to agricultural marketing as it promotes income maximization. Government and NGOs should assist in providing marketing information through television as it influences income maximization positively.

Recent R-Blogs

Introduction In the 933 days since the first COVID-19 case was reported on February 29, 2020 in Nigeria, about 267,511 cases have been recorded with 1.18% fatalities. Except for Kogi State which Government refused monitoring laboratories to be setup in her health facilities for confirming and managing COVID-19, cases have been recorded on regular basis in the other 35 states and Abuja, the Federal Capital. However, the frequency of cases vary from state to state.

Load library and the data The data is scrapped from the website of the Nigerian Centre for Disease Control (NCDC) i.e (NCDC 2020). The scrapping was done with some bits of tricks. Please see my post on that. The BREAKS were established from the visual inspection of the data (see (Nmadu, Yisa, and Mohammed 2009)) library(tidyverse) library(splines) library(Metrics) library(scales) library(readxl) library(patchwork) library(Dyn4cast) BREAKS <- c(70, 131, 173, 228, 274, 326) z.

Introduction The advent of the COVID-19 pandemic really put everyone in confusion and as the days, weeks went-by, everyone was trying to understand the trend and the direction of the incidence. While the medicals were in their labs trying to understand the anatomy of the various, various statisticians and data scientists were trying to model the trend so as to guide future actions and preparations. One of the early models was done for Australia by (Krispin and Byrnes 2020).

Software

Time-varying dynamic forecast, machine learning metrics, linear systems transformation, Mallow’s Cp of economic data for …

Recent Posts

Accomplish­ments

Introduction to data Scieence

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E-Platform on Weather and Climate Services for Resilience development: A Guide for Practitioners and Policy makers

Certified VIRT2UE Traine

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Practical General Equilibrium Modelling with GAMS

Advanced Leadership Seminar

Experience

 
 
 
 
 

Professor

The Federal University of Technology

Oct 2006 – Present Minna

Responsibilities include:

  • Teaching, Research and Community Development
  • Head of Department
  • Director and industrial Liaison Officer
  • Dean of Faculty
  • Consultancies, Networking and Collaborations
 
 
 
 
 

Chief Lecturer

The Federal Polytechic

Jan 1992 – Sep 2006 Bida
Lecturing, Research and Community Development.

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