The gains from working before starting a graduate program
I am frequently asked whether students should work before going to
graduate school. Of course, no single answer fits all, but I owe much of
my success to the experience I gained working before graduate school.
I grew up in a low-income family in Israel and went to a warm and friendly neighborhood school, then to a very demanding high school (Leyada) where I gained a sound foundation in math and critical thinking. After high school, I went for more than three years to the army. During my army term, I lived and worked in a kibbutz, an agricultural collective village. I could not have guessed that I would later become an agricultural economist, but in the kibbutz, I worked ploughing and cultivating fields, picking apples, moving irrigation pipes, and removing dead chicken from a highly automated poultry farm. I gained many insights here that became very helpful later in my career as an agricultural economist. I realized the importance of precision in modern agriculture. If a farmer is too late to discover a pest, much of her crop will be gone, and if she does not pay attention, she may end up destroying half the crops that could have been saved through timely weed control activities. Another lesson was that differences in abilities among workers can result in an incredible difference in productivity, and that even small amounts of the right training may make you a much better farmer. I realized how boring and tough some activities like weeding could be, and learned to appreciate the technologies we had that could replace or make these tasks easier. Technological change was very salient during the four years I stayed in the Kibbutz. Plastic irrigation pipes on wheels replaced the massive aluminum pipes, and new tractors and attached machinery allowed farmers to more comfortably and precisely plow and prepare fields for growing cotton. We were trained in the use of these advanced technologies and after a period of adjustment, we were able to get much better results using them.
After the army, I considered studying mathematics and physics as my undergraduate major, but I knew that I could not afford to study full time. I needed to support myself while in school, so I chose “easier” majors – economics and statistics. I simultaneously started working, selling advertisements for the “Blue Book,” a predecessor of the Yellow Pages in Israel. I did this for four months, and I gained a good foundation in sales. I realized that selling is hard work – walking for hours (I destroyed two pairs of shoes during these few months), thinking rigorously about how to pitch your product and adapt it to your customer, and getting rejected most of the time (frequently rudely). Later I realized that the ability to persevere after rude rejection is an essential skill of an academic economist. I also gained some insight into the way my customers made their buying decisions. Every potential buyer of advertisements wanted to know which of their competitors had bought ads. My mother’s uncle was a leading accountant and purchased a big advertisement from me. That impressed many other accountants and opened doors, but didn’t necessarily lead to sales. Each accountant assessed how the advertisement might serve them and made their choices accordingly.
These experiences served me years later as I started to study the economics of technology adoption. We consider adoption to understand events such as the spread of the Green Revolution and to conceptualize how to bring farmers to adopt technologies like integrated pest management that may enhance sustainability.
The dominant view until the 1980s was that adoption is a process of imitation. The paradigm assumes that people are homogenous; that they see others use a technology and then with some statistical likelihood, they will follow suit. The imitation model has been beneficial quantitively. It has allowed quite good estimation of the impact of changes in profitability of modern technology on the probability of its adoption. I did not doubt that the diffusion rate (percentage of farmers who adopt technology in a given moment) is an S-shaped function of time, as suggested by the imitation model. But I found the imitation narrative unrealistic and less useful for practical technology introduction efforts. I contributed to developing an alternative approach to understand adoption behavior. The key elements of this model are (1) heterogeneity among potential adopters – in terms of skills assets and preferences – and how it contributes to differences in the timing of adoption of technologies; (2) individual economic decision-making that includes several elements: awareness of the technology (individuals are affected by what others do), assessment based on perceived impact of the technology on well-being; and (3) dynamic processes that make technologies cheaper (for example, learning by doing, learning by using, etc). This approach suggests that the people who gain most from adoption are the earliest to adopt and as the technology becomes cheaper and its benefits improve, others join in. It also suggests that in early stages, individuals may not buy new technologies but rent them instead. It further suggests that marketing efforts that reduce the risk that the technology won’t fit individual needs and that increase access to credit are crucial. While myself and others have proven these points mathematically and with empirical evidence, my experience as a salesperson and later in computers provided me with several practical insights which laid the basis for this work.
I worked as sales person for four months, and at the same time took a class in a computer language IBM 360 Assembler and was hired by Koor Computers. The head of the company was Mr. Karpol, a colorful person with 3 missing fingers, who started his career as a construction worker, became a bookkeeper, and later designed computer systems. We had more than 100 clients and provided several packages including billing, inventory management, and payroll. After a few months, I became responsible for the payroll system. The system included a program that assessed input to prevent mistakes in the data, a program that updated the major files and computed salaries, and a third program that produced reports that were sent to the IRS, pension funds, banks, etc. My main job was to update the system as technology improved, oversee about 20 people that were working with clients making sure that there were no complaints, and to work with Mr. Karpol and others to acquire new customers and grow our business. Our salespeople met representatives of the client companies and when they needed a new type of computation, they would tell us and we would write a program to solve this problem. We charged the company for the cost of the program, but once we had written the program, we added it to expand our offering to all of our clients. So over time, we significantly expanded the range of services that we offered our clients, generally reducing their cost and improving their services.
During my five years working for Koor, we also took advantage of improving computer technology to develop new applications that linked billing, inventory, and payroll, and also allowed activities like cost accounting. This experience taught me a few things about the economics of scale and scope that are used in modern business. Once a company writes code and develops the capacity to address a problem, it has human and physical capital that are mostly fixed costs. The management of the company dreams how to take advantage of this new capacity and how to adapt it to increase sales. It is like diffusion of technology on the supply side – first a technology is introduced and then the supplier thinks who the most likely to groups are to adopt it and modifies it so they will be tempted to try it and buy it. This way of thinking allowed me to understand the way that supply chains operate.
The basic dynamics of an organization include refining a basic concept, then building capabilities, human capital, and relationships to provide a certain product or service as the foundation for an organization, and finally expanding and adapting them over space and time to grow. This process is conducted by companies like McDonalds, who took several years to develop a basic concept, first spread nationally and then internationally, and then modified their products to accommodate changes in technologies and preferences. It also applies to food chains like Walmart, computer companies like Apple, and tractor manufacturers like John Deere.
The specifics vary in every sector. Even in our little computer company, I learned how the manager needs to address issues of credit and how the company’s ability to grow depends on this. I also learned how market decisions can affect the company’s ability to grow. When I started studying adoption and I noticed that most of the literature ignored marketing, I realized that this was one area that I could emphasize in my own research. Thus when I teach students about Apple, I emphasize that the genius of Apple is not only offering a better product, but also the better store and their marketing arrangements. That emphasizes the importance of both technical and managerial excellence.
Perhaps the main lesson from working during my time at university was that while I enjoyed my life in the corporate world, that it’s not ideal for me. It was rewarding financially and exciting for a while, but I realized that while I loved programming and system design, the main challenge was to understand the behavioral and economic aspect, and a PhD in applied economics would expand my horizons and make me happier. That motivated me to make many sacrifices and go to a PhD program. Everyone is different, but at least my experience suggests that working while going to undergraduate school and maybe between undergraduate and graduate school is important. I considered living and working as part of the “applied research” that one needs to engage in, before committing to a graduate program.
I grew up in a low-income family in Israel and went to a warm and friendly neighborhood school, then to a very demanding high school (Leyada) where I gained a sound foundation in math and critical thinking. After high school, I went for more than three years to the army. During my army term, I lived and worked in a kibbutz, an agricultural collective village. I could not have guessed that I would later become an agricultural economist, but in the kibbutz, I worked ploughing and cultivating fields, picking apples, moving irrigation pipes, and removing dead chicken from a highly automated poultry farm. I gained many insights here that became very helpful later in my career as an agricultural economist. I realized the importance of precision in modern agriculture. If a farmer is too late to discover a pest, much of her crop will be gone, and if she does not pay attention, she may end up destroying half the crops that could have been saved through timely weed control activities. Another lesson was that differences in abilities among workers can result in an incredible difference in productivity, and that even small amounts of the right training may make you a much better farmer. I realized how boring and tough some activities like weeding could be, and learned to appreciate the technologies we had that could replace or make these tasks easier. Technological change was very salient during the four years I stayed in the Kibbutz. Plastic irrigation pipes on wheels replaced the massive aluminum pipes, and new tractors and attached machinery allowed farmers to more comfortably and precisely plow and prepare fields for growing cotton. We were trained in the use of these advanced technologies and after a period of adjustment, we were able to get much better results using them.
After the army, I considered studying mathematics and physics as my undergraduate major, but I knew that I could not afford to study full time. I needed to support myself while in school, so I chose “easier” majors – economics and statistics. I simultaneously started working, selling advertisements for the “Blue Book,” a predecessor of the Yellow Pages in Israel. I did this for four months, and I gained a good foundation in sales. I realized that selling is hard work – walking for hours (I destroyed two pairs of shoes during these few months), thinking rigorously about how to pitch your product and adapt it to your customer, and getting rejected most of the time (frequently rudely). Later I realized that the ability to persevere after rude rejection is an essential skill of an academic economist. I also gained some insight into the way my customers made their buying decisions. Every potential buyer of advertisements wanted to know which of their competitors had bought ads. My mother’s uncle was a leading accountant and purchased a big advertisement from me. That impressed many other accountants and opened doors, but didn’t necessarily lead to sales. Each accountant assessed how the advertisement might serve them and made their choices accordingly.
These experiences served me years later as I started to study the economics of technology adoption. We consider adoption to understand events such as the spread of the Green Revolution and to conceptualize how to bring farmers to adopt technologies like integrated pest management that may enhance sustainability.
The dominant view until the 1980s was that adoption is a process of imitation. The paradigm assumes that people are homogenous; that they see others use a technology and then with some statistical likelihood, they will follow suit. The imitation model has been beneficial quantitively. It has allowed quite good estimation of the impact of changes in profitability of modern technology on the probability of its adoption. I did not doubt that the diffusion rate (percentage of farmers who adopt technology in a given moment) is an S-shaped function of time, as suggested by the imitation model. But I found the imitation narrative unrealistic and less useful for practical technology introduction efforts. I contributed to developing an alternative approach to understand adoption behavior. The key elements of this model are (1) heterogeneity among potential adopters – in terms of skills assets and preferences – and how it contributes to differences in the timing of adoption of technologies; (2) individual economic decision-making that includes several elements: awareness of the technology (individuals are affected by what others do), assessment based on perceived impact of the technology on well-being; and (3) dynamic processes that make technologies cheaper (for example, learning by doing, learning by using, etc). This approach suggests that the people who gain most from adoption are the earliest to adopt and as the technology becomes cheaper and its benefits improve, others join in. It also suggests that in early stages, individuals may not buy new technologies but rent them instead. It further suggests that marketing efforts that reduce the risk that the technology won’t fit individual needs and that increase access to credit are crucial. While myself and others have proven these points mathematically and with empirical evidence, my experience as a salesperson and later in computers provided me with several practical insights which laid the basis for this work.
I worked as sales person for four months, and at the same time took a class in a computer language IBM 360 Assembler and was hired by Koor Computers. The head of the company was Mr. Karpol, a colorful person with 3 missing fingers, who started his career as a construction worker, became a bookkeeper, and later designed computer systems. We had more than 100 clients and provided several packages including billing, inventory management, and payroll. After a few months, I became responsible for the payroll system. The system included a program that assessed input to prevent mistakes in the data, a program that updated the major files and computed salaries, and a third program that produced reports that were sent to the IRS, pension funds, banks, etc. My main job was to update the system as technology improved, oversee about 20 people that were working with clients making sure that there were no complaints, and to work with Mr. Karpol and others to acquire new customers and grow our business. Our salespeople met representatives of the client companies and when they needed a new type of computation, they would tell us and we would write a program to solve this problem. We charged the company for the cost of the program, but once we had written the program, we added it to expand our offering to all of our clients. So over time, we significantly expanded the range of services that we offered our clients, generally reducing their cost and improving their services.
During my five years working for Koor, we also took advantage of improving computer technology to develop new applications that linked billing, inventory, and payroll, and also allowed activities like cost accounting. This experience taught me a few things about the economics of scale and scope that are used in modern business. Once a company writes code and develops the capacity to address a problem, it has human and physical capital that are mostly fixed costs. The management of the company dreams how to take advantage of this new capacity and how to adapt it to increase sales. It is like diffusion of technology on the supply side – first a technology is introduced and then the supplier thinks who the most likely to groups are to adopt it and modifies it so they will be tempted to try it and buy it. This way of thinking allowed me to understand the way that supply chains operate.
The basic dynamics of an organization include refining a basic concept, then building capabilities, human capital, and relationships to provide a certain product or service as the foundation for an organization, and finally expanding and adapting them over space and time to grow. This process is conducted by companies like McDonalds, who took several years to develop a basic concept, first spread nationally and then internationally, and then modified their products to accommodate changes in technologies and preferences. It also applies to food chains like Walmart, computer companies like Apple, and tractor manufacturers like John Deere.
The specifics vary in every sector. Even in our little computer company, I learned how the manager needs to address issues of credit and how the company’s ability to grow depends on this. I also learned how market decisions can affect the company’s ability to grow. When I started studying adoption and I noticed that most of the literature ignored marketing, I realized that this was one area that I could emphasize in my own research. Thus when I teach students about Apple, I emphasize that the genius of Apple is not only offering a better product, but also the better store and their marketing arrangements. That emphasizes the importance of both technical and managerial excellence.
Perhaps the main lesson from working during my time at university was that while I enjoyed my life in the corporate world, that it’s not ideal for me. It was rewarding financially and exciting for a while, but I realized that while I loved programming and system design, the main challenge was to understand the behavioral and economic aspect, and a PhD in applied economics would expand my horizons and make me happier. That motivated me to make many sacrifices and go to a PhD program. Everyone is different, but at least my experience suggests that working while going to undergraduate school and maybe between undergraduate and graduate school is important. I considered living and working as part of the “applied research” that one needs to engage in, before committing to a graduate program.
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